In our work on Labour Market Information Systems, we frequently talk about the differences between labour market information and labour market intelligence in terms of making sense and meanings from statistical data. The graph above is a case in point. It is one of the outcomes of a survey on Graduate Employment, undertaken by the UK Higher Education Statistics Agency (HESA).

Like many such studies, the data is not complete. Yet, looking at the pay by gender reveals what WONKHE call “a shocking picture of the extent of the pay gap even straight out of university, and how different subject areas result in a diverse range of pay differences.”

Understanding why there is such a gap is harder. One reason could be that even with equal pay legislation, employers simply prefer to employ male staff for higher paid and more senior jobs. Also, the graph shows the subject in which the students graduated, not the occupational area in which they are employed. Thus the strikingly higher pay for mean who undertook nursing degrees may be due to them gaining highly paid jobs outside nursing. Another probable factor in explaining some of the pay gap is that the figures include both full and part time workers. Nationally far more women are employed part time, than men. However, that explanation itself raises new questions.

The data from HESA shows the value of data and at the same time the limitations of just statistical information. The job now is to find out why there is such a stark gender pay gap and what can be done about it. Such ‘intelligence’ will require qualitative research to go beyond the bald figures.

In a new fact sheet the Tech Partnership reveals that UK cyber workforce has grown by 160% in the five years to 2016. 58,000 people now work in cyber security, up from 22,000 in 2011, and they command an average salary of over £57,000 a year – 15% higher than tech specialists as a whole, and up 7% on last year. Just under half of the cyber workforce is employed in the digital industries, while banking accounts for one in five, and the public sector for 12%.

Interest in Vocational Education and Training (VET) seems to go in cycles. Its always around but some times it is much more to the forefront than others as a debate over policy and practice. Given the pervasively high levels of youth unemployment, at least in south Europe, and the growing fears over future jobs, it is perhaps not surprising that the debate around VET is once more in the ascendancy. And the debates over how VET is structured, the relation of VET to higher education, the development of new curricula, the uses of technology for learning, the fostering of informal learning, relations between companies and VET schools, the provision of high quality careers counselling and guidance, training the trainers – I could go on – are always welcome.

Whilst in some countries like the UK deregulation seems to have created many jobs, most of these are low paid and insecure.

Higher productivity requires innovation and innovation is in turn dependent on the skills and knowledge of the workforce. But in a time of deregulation there is little incentive for employers to invest in workforce training.

There are signs that some companies are beginning to realise they have a problem. There has been a notable interest from a number of large companies in supporting new apprenticeship programmes and not just in the German speaking countries. In Spain the recently launched Alliance for FP Dual is making slow but steady progress in persuading companies to support the FP Dual alternance or apprenticeship programme. There remain many obstacles, not least the continuing austerity programme, political instability and the perilous financial position of many small and medium enterprises. I will talk more about some of these issues in forthcoming articles on this web site, coming out of the findings of a  small research project in Valencia sponsored by the International Network on Innovative Apprenticeship (INAP).

But to be successful initiatives like the Spanish FP Dual and the wider EU backed Alliance for Apprenticeships have to be linked to wider programmes to promote innovation. Without some degree of labour market regulation this is going to be hard to achieve.

There is a lot of speculation at the moment as to the jobs of the future. On the one hand, it is said that we are educating young people for jobs which do not yet exist; on the other hand there are dire predictions that up to of existing 55 per cent of jobs may disappear to automation in the next five years.

If it is hard as a researcher who works with labour market data to make sense of all this, imagine what it is like for young people trying to plan a career (and if doing a degree in the UK, running up major debt).

However, there is beginning to appear some more nuanced research on the future of jobs. Michael Chui, James Manyika, and Mehdi Miremadi have just published the initial report on a research project looking at how automation will affect future employment. The report, entitled ‘Where machines could replace humans—and where they can’t (yet)’, is based on detailed analysis of 2,000-plus work activities for more than 800 occupations. Using data from the US Bureau of Labor Statistics and O*Net, they have quantified both the amount of time spent on these activities across the economy of the United States and the technical feasibility of automating each of them.

Their overall finding is that while automation will eliminate very few occupations entirely in the next decade, it will affect portions of almost all jobs to a greater or lesser degree, depending on the type of work they entail.

Each whole occupation is made up of multiple types of activities, each with varying degrees of technical feasibility. In practice, they explain, automation will depend on more than just technical feasibility. Five factors are involved: technical feasibility, costs to automate, the relative scarcity, skills and costs of workers who might otherwise do the activity, benefits (e.g. superior performance) of automation beyond labour costs substitution and regulatory and social acceptance considerations.
The likelihood and ease of automation depends on the types of activities organised on a continuum of less susceptible to automation to more susceptible to automation: managing others, applying expertise,  stakeholder interactions, unpredictable physical work, data collection, processing data, predictable physical work. Thus occupations like accommodation, food service and manufacturing which include a large amount of predictable physical work are likely to be automated, similarly work in finance and insurance which involves much processing of data. On the other hand jobs in construction and in agriculture which comprise predominantly unpredictable physical work are unlikely to be automated, at least at present. And there is good news for teachers: “the importance of human interaction is evident in two sectors that, so far, have a relatively low technical potential for automation: healthcare and education.”

Like very much this announcement in the Media, Communications and Cultural Studies Association (MeCCSA) list server:

Dr Ergin Bulut is an assistant professor at Koc University in Turkey. He will start his IAS fellowship on 1 June 2017. It will focus on the analysis of labour conditions in the video game industry. Dr Bulut comments on the importance of studying the digital game industry: “There is much hype regarding the potentials of creative economy and creative production. Young people tend to regard video game development as a dream job. Our society also preaches that young people should do what they love and be ready to work for free if they really want to have a job in the video game industry or other creative industries. An inquiry of the game industry enables us to understand both the pleasures and pains of game development and interrogate the politics of this ‘dream job’ discourse”.

It seems every event about start up businesses I go to focuses on computers and Information Technology as the golden answer for young people and work opportunities in the future. I don’t have the figures to hand but I read in an EU report that the average (mean, I think) wage for those developing mobile apps in the UK is something like £12,000 a year and it is little more in most EU countries.

There seems a fairly wide disjunction between young people’s perceptions and the reality of opportunities and employment in different jobs.About five years ago I ran a focus group in a careers centre in Kent in England. I asked the young people in the panel how they found out about possible careers. They looked at me as if I was stupid – its obvious sir, they said. We look it up on Google. Research suggests most people rarely go beyond the first page of listings on any Google search. And then, as now, queries about how much pay you can hope to make frequently push sites to the top which are merely trying to gather data and give wildly improbable results based on very little data. It was this experience which led us to become involved in the UKCES LMI for All project which seeks to provide access to a range of quality labour Market Information and can be used to develop a variety of different applications. But good though LMI for All is research like that outlined above in a range of different occupations would be invaluable in helping to understand why young (and not so young) people choose their careers. (And I love the title!).

High or low skills? Graduate job or not?

For a number years now I have been working on projects developing the use of open data for careers counselling, advice and guidance. This work has been driven both by the increasing access to open data but also by the realisation of the importance of Labour Market Information (LMI) for those thinking about future education and / or jobs. And of course with high levels of job insecurity, such thinking becomes more urgent and in an unstable economy and labuor market, more tricky.

Yet even if we clean the data, add it to a database, provide and open API for access and develop tools for data visualisation, interpretation is still not easy. Here is one case, taken from this mornings Guardian newspaper.

Although the article is using the chart to show the rapid growth in knowledge intense occupations, I am not sure it does. Assuming that these are percentage change based on the original job totals, it probably show growth in low skilled jobs is far outstripping high skilled work, especially in the last 12 months. And that is taking into account that (once again probably) most job loss due to technology is focused din low skilled areas – e.g the quoted 70,00 jobs lost in supermarket check outs due to automation.

I am also interested to see from wonkhe that “The Higher Education Statistics Agency (HESA) who have been running the Destination of Leavers Survey (DLHE) and its predecessors for 21 years, are now consulting widely on the future of assessing graduate outcomes.” For some time now there has been disquiet about the numbers of graduates working in ‘non graduate’ jobs. And that raises questions – just like the graph above focusing on high skills occupations – on just what a graduate job is. André Spicer, professor of organisational behaviour at the Cass Business School, City University London has cited “studies suggesting that the jobs which require degree-educated employees have peaked in 2000 and may be going down” and notes that many people apparently employed for their high-level specialist skills end up doing sales and marketing or fairly routine generalist work.

All this of course is highly subversive. Officially we are moving towards a high skilled economy needing more graduates and requiring higher level apprenticeships. My feeling in country slick Spain with high youth unemployment is what we need are apprenticeships in areas like construction and hospitality – both because they are sectors which can provide employment and also where higher skills are desperately needed to improve quality and productivity. Yet for governments there is an awful temptation to launch programmes in new ‘sexy’ areas  like games technologies despite the scarcity of jobs in these fields.

The debate over the future of work, long running in research circles but kicked into public consciousness amongst others a Oxford University study titled ‘The Future of Employment: How susceptible are jobs to computerisation’ suggesting over 40 per cent of jobs are at threat in the next 11 years due to technology, continues. In truth there is little agreement from economists and labour market specialists. Some claim techn0logy is leading to more jobs, some that it is destroying jobs and still other that it is neutral. Some claim technology is leading to jobs being deskilled, others the reverse.

I like a recent blog post entitled ‘More on digitalisation and skills: What happens within occupations?’, by Guillermo Montt on the OECD Skills and Work web site. The article says that “as technology enters the workplace, the tasks related to a job and an occupation change” citing  Alexandra Spitz-Oener (2006) who found that in Germany, occupations in the 2000s require more complex skills than in 1979 and that this change is more pronounced in occupations that adopted computers. Although something of a simplification, that finding is largely born out in analysis of the USA O*NET data. The article also draws attention to research by James Bessen published in his recent book ‘Learning by Doing: The Real Connection between Innovation, Wages and Wealth‘. “He follows the evolution of occupations over time and claims that accelerated technological change has implications for inequality within occupations with more and more occupations becoming winner-take-all markets.” Essentially, as new technology is introduced pay and opportunities in occupations bifurcate with a few taking high high, pay levels and more taking home lower pay. “In occupations requiring above-median computer use, the 90th to 50th percentile wage ratio has risen by 0.2% per year but has remained stagnant in occupations with below-median computer use. Workers who stay ahead of the curve, those who learn by doing, reap the wage benefits of technological change.”

This has major implication for training and continuing professional development. CPD has traditionally been organised through courses. But as we have already found in in the EmployID project working with employees in European Public Employment Services, traditional course delivery is both too slow to respond to change and even more problematic is unable to deliver the volume of training required. The approach adopted in EmployID is both to look at using new technologies for learning and for promoting informal learning in the workplace but also to center on changing occupational identities. For instance there is a very different occupational identity associated with a print graphic designer than todays web designer. But the ability to change occupational identities may be shaped by previous learning experiences and by motivation as well as the ability to reflect on both individual and group learning. Within EmployID we are exploring how Learning Analytics can bets be deployed to assets people in reflection (Reflection Analytics) and to assist in transforming identities to deal with such change. I am presenting this work next week at a LAKs pre conference workshop in Glasgow and will publish by slides on this blog.

I like this blog post by Robert Peal entitled ‘A Myth for Teachers: Jobs That Don’t Exist Yet’. The article looks at the origins of the idea that the top 10 in-demand jobs in 2010 didn’t exist in 2004 and its later variant that 60 per cent of the jobs for children in school today have not been invented. In both cases he found it impossible to track these statement in any reliable research. Of course these are myths. But often such myths can be tracked back to quite prosaic political objectives.

For a long time, the European Union has pushed the idea of the knowledge society. And whilst there are many learned papers describing in different ways what such a society might look like or why such a society will emerge there is little evidence of its supposed impact on labour markets. Most common is the disappearance of low and unskilled jobs, linked to growing skill shortages in high skilled employment. Yet in the UK most recent growth in employment has been in low skills, low paid jobs in the retail sector. I remember too in the late 1990s when the European industry lobby group for computers were preaching dire emergencies over the shortage of programmers, with almost apocalyptic predictions of what would happen with the year 200 bug if there were not major efforts to train newcomers to the industry. Of course that never happened either and predictions of skills shortages in software engineering persist despite the fact the UK government statistics show programmers pay falling in the last few years.

I’ve been invited to do several talks in the last year on the future of work. It is not easy. There are two lengthy reports on future skills for the UK – ‘Working Futures 2012- 2022’ and ‘The future of work: jobs and skills in 2030’, published by the UK Commission for Skills and Industry. Both are based on statistical modelling and scenario planning. As one of the reports says (I cannot remember which) “all models are wrong – it is just that some of more useful than others. Some things are relatively clear. There will be a big upturn in (mainly semi skilled) work in healthcare to deal with demographic changes in the age of the population. There will also be plenty of demand for new skilled and semi skilled workers in construction and engineering. Both are major employment sectors and replacement demand alone will result in new job openings even if they do not expand in overall numbers (many commentators seem to forget about replacement demand when looking at future employment).

But then it all starts getting difficult. Chief perhaps amongst this is possible disruptions which can waylay any amount of economic modelling. The following diagram above taken from ‘The future of work: jobs and skills in 2030’ shows possible future disruptions to the UK economy and to future jobs. One of these is the introduction of robots. With various dire reports that up to 40 per cent of jobs may disappear to robots in the next few years, I suspect we are creating another myth. Yes, robots will change patterns of employment in some industries, and web technologies enable disruptions in other areas of the economy. Yet much of the problems with such predictions lay with technological determinism – the idea that technology somehow has some life of its own and that we cannot have any says over it. At the end of the day, despite all the new technologies and the effects of globalization, there are massive policy decisions which will influence what kind of jobs there will be in the future. These include policies for education and training, inter-governmental treaties, labour market and tax policies, employment rights and so on. And such considerations should include what jobs we want to have, how they are organised, where they are and the quality of work. At the moment we seem to be involved in a race to the bottom – using the excuse of austerity – which is a conscious policy – to degrade both pay and work conditions. But it doesn’t need to be like this. Indeed, the excuses for austerity may be the biggest myth of all.

From OECD:

PISA in Focus shows, in many countries the teaching profession is having a hard time making itself an attractive career choice – particularly among boys and among the highest-performing students.

PISA 2006 asked students from the 60 participating countries and economies what occupation they expected to be working in when they are 30 years old. Some 44% of 15-year-olds in OECD countries reported that they expect to work in high-status occupations that generally require a university degree; but only 5% of those students reported that they expect to work as teachers, one of those professional careers.

The numbers are even more revealing when considering the profile of the students who reported that they expect to work as teachers. If you read our report on gender equality in education published earlier this year, you may remember that girls tend to favour “nurturance-oriented” careers more than boys do – and teaching is one of those careers. In almost every OECD country, more girls (6%) than boys (3%) reported that they expect to work as teachers. This statistic is particularly worrying when you recall that the majority of overall low achievers in school are boys, who could benefit from the presence of more male role models at school.