The government published research from its Skills and Productivity Board on Wednesday along with the first set of data for the new Unit of Future Skills.
The Skills and Productivity Board was set up in October 2020 and included a team of labour market economists who gave advice on how courses and qualifications should align to the skills that employers’ need post-Covid-19.
Before Wednesday no findings had been published by the board.
The SPB has now wound up and been replaced by the Unit for Future Skills. The research conducted over the last two years has finally been published, ahead of this transition.
Below is a summary of the SPB’s long-awaited research and more information on the Unit of Future Skills’ first data release.
The SPB commissioned a consultancy called Frontier Economics to assess the usefulness of skills taxonomies.
Skills taxonomies can be used as a framework by which to measure the demand for the skills by employers, the current supply of those skills from workers, and the potential supply based on courses offered by education providers and employers.
The board found the best taxonomy to use is called O*NET, which was developed by the US Department of Labor.
However, there might be some gaps in information with O*NET as it prioritises analysis of broad skills, with attributes summarised in a smaller number of measures than in other taxonomies.
So, Frontier Economics suggested where needed, taxonomies such as those developed by Nesta and ESCO present skills at a very granular level, could be used to plug these gaps.
Research from Kenneth Mayhew looked at “lagging areas” and how levelling up initiatives will need to be tailored to the different needs of different localities.
It presented a list of items which the DfE might want to “keep in mind” as they develop future work programmes.
The report explored the problems faced by lagging areas – noting “there is rarely, if ever, one single problem, which if addressed, will significantly transform the fortunes of a locality”.
It also explored the role of skills in levelling up strategies – calling for the DfE to ask a series of questions around local skills improvement plans and saying the department should make use of taxonomies to understand local problems and solutions.
Possible initiatives which could benefit lagging areas were outlined – such as more policy-orientated work on how to ensure teacher quantity and quality in some of the UK’s more deprived areas.
The report also noted the “inadequacy of careers advice to secondary school students and adults” and argued there is scope for research on the extent to which it varies by locality and on what can be done to improve it.
This report explored how investments in education or skills in poorer performing areas could improve productivity.
A key part of this research was an analysis that used the longitudinal education outcomes dataset.
Findings were that there are very high returns to qualifications, in terms of both employment and earnings.
For example, reaching level 2 – something almost one in six people under 27 do not do – increases the probability of employment for women (men) by around 19 (10) percentage points and earnings by around 22 per cent (13 per cent).
The returns from qualifications are higher in areas of the country that are economically poorer performing.
Researchers found that reaching level 2 increases employment prospects for women (men) by around 25 (13) percentage points for individuals living in areas in the bottom quartile based on the Index of Multiple Deprivation (IMD, the 25 per cent most deprived areas of the country), but only around 18 (8) percentage points in other areas.
Another key finding was that investment in skills alone is unlikely to be sufficient to ‘level up’ economically poorer performing areas.
The analysis found that the returns from education in poorer performing areas are strong, with the benefits of upskilling highly likely to remain within those areas, highlighting the importance of skills investments for the levelling up agenda.
This paper used existing knowledge and research to explain why there is variation in productivity across the country and the role that skills played in these variations.
It posed a range of questions about where national skills policy could go next in relation to the agenda around levelling up productivity.
Recommendations included a call for the DfE to map and seek a greater understanding of existing local skills initiatives and institutions and find ways to disseminate examples of good practice.
The report said the DfE should think about the future systems architecture and governance of skills policy – and how skills policy can best be conceived of and delivered in a more joined up way across traditional divisions or silos within the department.
A strong emphasis should be placed on local aspects of the work of the Unit for Future Skills, the report said, arguing that it will need to gather and analyse high quality and granular labour market information that can inform decision making at local levels.
The report also said consideration should be given to evaluation of the skills work of combined authorities, and considered alongside the planned evaluation of LSIP trailblazers.
This report sought to support the development of the new Unit for Skills which aims to improve the quality, quantity and accessibility of labour market information.
Researchers highlighted the key labour market information gaps and opportunities, and illustrated where improvements could be made.
They outlined a number of priorities for improvements to LMI on skills that the DfE should tackle.
For example, the report said that local level data on demand is currently poor but should be a priority for improvement.
It suggests that web-scraping could be used to provide a direct indication of skills in demand, rather than relying on indicators of demand at the occupation level.
In terms of supply, data on the stock of skills within the workforce is also limited, according to the report. This is a barrier to identifying where to invest to raise productivity.
In terms of suggestions, the paper highlighted the need for a skills taxonomy.
“UFS should help to develop a common language and taxonomy of skills that can be used consistently throughout the skills system to strengthen the link between qualifications and skills produced for the labour market,” the report said.
This report is an overview of the Skills and Productivity Board’s work to document the skills needs of the economy now and in future, with a view to identifying skills mismatches and growing areas of skills needs.
It identifies a set of ‘core transferable skills’ that are currently in high demand across many occupations and that are likely to continue being in high demand in the future.
These include communication skills, digital and data skills, application of knowledge skills, people skills, and mental processes.
The SPB said that because these skills are valuable across a wide range of jobs, firms have weaker incentives to invest in them than in firm-specific skills.
“Investing in the development of these core transferable skills is therefore likely to be worthwhile for the government,” the report added.
The report identified skills that are growing in importance and used across many occupations in the economy.
These included people skills, mental processes and application of knowledge skills, and skills associated with being able to teach others and be a good learner.
Skills that are growing in importance, even though they are used in relatively fewer occupations, include STEM knowledge (particularly relevant for Health and Science and Technology occupations, and already likely to be in shortage now), care skills, important for Health occupations, and a range of management skills.
The Unit for Future Skills is an analytical and research unit within the DfE.
It has been set up to improve the quality of jobs and skills data, and builds on the analysis and research of the Skills and Productivity Board.
This week, the unit published data on the type of employment people undertake after training.
This data can be accessed through four dashboards – including the Career pathways dashboard, Graduate outcomes dashboard, Further education outcomes dashboard and the 16 to 18 qualifications dashboard.
The FE dashboard shows qualification level, employment and earnings outcomes data for apprenticeships and adult further education.
And the 16 to 18 qualifications dashboard shows detailed qualification level, employment and learning outcomes for 16 to 18 year olds finishing study at further education institutions.