Skills are crucial to boosting productivity – but they cannot do the job alone

Arun Advani and Claire Crawford

Today marks the launch of the Department for Education’s new Unit for Future Skills (UFS). Its remit is to use existing data – and champion the creation of new data – to better understand the skills businesses want and whether the education and training system is delivering them.

A focus of the UFS is to improve understanding of ‘skills mismatches’ – the gaps between the demand for and supply of different skills. The idea is that by learning more about skills mismatches and, crucially, their sources, we can design more effective policies to close these gaps, and hence raise productivity.

The UFS was the brainchild of the current Secretary of State for Education, Nadhim Zahawi. Its origins, though, lie at least in part in the Skills and Productivity Board (SPB), set up by the former Secretary of State for Education, Gavin Williamson, to investigate both skills mismatches and how skills contribute to productivity. The SPB comes to an end as the UFS launches.

This apparent change in remit between the UFS and its predecessor is an important one. While the focus of the new unit on collating and sharing data is undoubtedly welcome, the loss of the explicit link to productivity risks losing the ‘bigger picture’ rationale for such a unit.

Part of our work on the SPB – on which we sat alongside four other academic experts – was to provide some initial insights into the skills which seemed to have significant mismatches between demand and supply, or for which demand was likely to grow over time.

Unfortunately, the data at our disposal were not well suited to identifying skills mismatches, and we made a series of recommendations to the Secretary of State about the ways in which the UFS could improve upon this. For example, information about the demand for skills is collected either using relatively small-scale national surveys or in different ways across different local areas, for example as part of the new Local Skills Information Plans, making granular information that is comparable across areas difficult to obtain. Instead, we had to infer the demand for skills by combining information on the number of jobs in different occupations in the economy with the importance of each skill in those occupations.

The difficulties in identifying the supply of skills were even greater: while the Longitudinal Education Outcomes (LEO) data provides excellent information about the qualifications of younger cohorts in England, there is no straightforward way of identifying which skills – rather than knowledge – different qualifications develop, and no way to reflect the skills that workers acquire – or indeed lose – through on-the-job training rather than in formal education.

Despite these challenges, our analysis highlighted some skills which seemed to be particularly important and potentially worthy of further investment by the government:

• We identified a set of ‘core transferable skills’ that are important across a large number of jobs in the economy now, and are expected to remain so in future. These skills included communication skills, people skills and ‘information skills’ – including decision-making, problem solving and critical thinking. Ensuring people have these skills means they should be equipped to perform a range of jobs well, and should also help them to transfer between jobs as needed.
• We also identified a set of skills that, despite being important for only a small number of jobs, seem to be in shortage now, and are valuable in occupations that contribute disproportionately to productivity. These include Science, Technology, Engineering and Maths (STEM) knowledge and the application of this knowledge, including scientific and mathematical reasoning.

The appropriate policy responses to these findings are not straightforward. While encouraging more people to study STEM subjects may be sensible for many reasons, it may not help fill STEM job vacancies: not if the main challenge is that these occupations pay a lot less – or have other less attractive job characteristics – than occupations in which those skills can be equally effectively applied and are rewarded more highly.

In bringing together richer skills and labour market data, the work of the UFS should enable us to better understand these issues and support the development of policies to eliminate these gaps. But an important question is how far eliminating skills mismatches – and indeed increasing skills more generally – can get us in terms of boosting productivity, especially in ‘left behind’ areas.

One potential risk of relying heavily on skills investments as a route to ‘levelling up’ is that higher skilled or more educated individuals may move away, meaning the areas in which the investments are made do not benefit fully from those investments. We already know this is the case for many graduates.

But our work suggests that, unlike graduates, those with lower level qualifications are highly likely to remain in or close to the areas in which they grew up. While around half of both graduates and non-graduates have moved at least locally by age 27, only one in six non-graduates moves to a different commuting area, compared to a one in three graduates. Amongst those who move, a majority of non-graduates move less than 5km, compared to more than 20km for graduates. This suggests that poorer performing areas would benefit from investments in skills, at least up to degree level.

Our work also suggests that while a substantial proportion (two-thirds) of the difference in wages (a proxy for productivity) across areas can be explained by the qualifications and skills of the individuals living in those areas, a significant minority (one-third) cannot. This highlights that investments in human capital (skills) on their own will not be enough to ‘level up’. Such investments will need to be supplemented with investments in other types of capital – the type and extent of which will differ from place to place – to ensure that the benefits of investments in education and skills can be fully realised.

Better data will help shed light on the extent of and reasons for skills mismatches, and hopefully lead to policies aimed at addressing these mismatches. However, reducing mismatches alone is unlikely to be sufficient to deliver the necessary boost to productivity if we are to eliminate differences across areas, or between the UK and its international competitors.

Without greater demand for skills, particularly in poorer performing areas of the country, we risk levelling down rather than levelling up. It is crucial that the UFS works closely with colleagues across government and in local areas to ensure that they support the ‘productivity’ as well as the ‘skills’ part of the board they are replacing.