Improving Lives Through Higher Education & Market Intelligence

Contents

3......Foreword by Gordon McKenzie of GuildHE

4......Introduction: Improving Lives Through Education

6......Contributing to Regional Productivity

10....Contributing to National Productivity

13....Getting Objective About Employability

16....Employability & Transferrable Skills

18....In Summary

About EmsiIn the modern economy, universities are increasingly expected to play the role not just of educators and researchers, but also of economic drivers. Emsi’s vision is to help universities achieve this role by connecting students into employment through education. Through a combination of robust market intelligence and easy-to-use tools, we give education institutions a better understanding of the needs of their region’s industry and employers, enabling them to plan a more demand-led course portfolio, and to direct students into sustainable careers. By working together, we are helping universities increase productivity in their region, and improve the employability of their students.

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Foreword

There are many reasons to go to university just as there are many benefits, direct and indirect, from being a graduate. But one reason has always been to get a particular, or better, or more interesting career – as Confucius said in the Analects, it was not easy to find someone who had studied for three years without aiming at pay.

But the shift in the funding of higher education towards fees backed by student loans has raised the stakes for both students and government. Faced by debt (or, effectively, a higher rate of tax) students are more interested in their likely career prospects. And government wants better graduate outcomes to keep down the cost of making the loans and to get higher tax receipts longer term.

This Emsi report sets out some practical steps universities could take to help enhance graduate employability and improve national productivity. It argues a clear line of sight between universities’ connections with industry, the impact on curriculum design, efforts to improve graduate employability, and regional and national productivity.

GuildHE’s members have a tradition of learning, research and innovation in industries and professions. These regionally focused, smaller or specialist institutions make a massive contribution in many areas including enhancing skills, productivity and social mobility.

This reflects successful working partnerships with professions, businesses and industry sectors, and the ability of these institutions to understand and adapt successfully to changes in industry practice and patterns of employment, and deliver highly skilled graduates ready for the workplace.

Good labour market intelligence, and knowing how to use it, can inform that understanding, can be a vital tool to help universities contribute more and more directly to increased productivity, and can help students and graduates better understand employer demand and how well they match-up against the skills required.

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Gordon McKenzieChief Executive of GuildHE

Introduction: Improving Lives Through Education

What is the purpose of education? In her article, Good Citizenship: The Purpose of Education1, Eleanor Roosevelt began by saying, “This question agitates scholars, teachers, statesmen, every group, in fact, of thoughtful men and women.” She was right, and no doubt if we were to survey universities with this question – both students and staff –, we would come up with huge array of answers. The purpose of education is to pass a body of knowledge on from one generation to the next. No, the purpose of education is to equip people to be able to think critically and analytically. No, the purpose of education is to equip people with the skills and knowledge that will help them to succeed in the world of work.

No doubt 101 other answers could be given, and many of them looking at first glance to be at odds with one another. Yet although the different answers given to the question can seem to be at variance, there is something of a false dichotomy occurring. It is obvious that some degrees, such as those in the liberal arts are, by and large, unlikely to be connected directly with a career. Yet does this mean they fail to pass on the kind of skills that make a person employable? Of course not. Likewise, it is obvious that other degrees, such as chemical engineering, are specifically designed to be linked with a particular career. But does this mean that they fail to teach critical thinking and analytical skills? Again, of course not.

There is actually more commonality running though most, if not all, definitions of the purpose of education than first meets the eye. Why would you want to pass a body of knowledge on from one generation to the next? Why would you want to equip people to be able to think? Why would you want to equip people with the skills and knowledge that will help them to succeed in the world of work? The answer to all these questions is that by doing so, you are hoping to improve lives – the lives of individuals, of communities and of society.

“Education for education sake”, and “education for careers sake”, although very different in their priorities, both align with the overarching concept of improving lives through education. And whilst most universities will cater for both approaches, albeit to a greater or lesser extent, there has undoubtedly been a shift in recent years towards the second approach. There are two important factors contributing to this shift.

Firstly, there are increasing calls for higher education to contribute more directly to the prosperity of the economy. For instance, in an article for The Economist2 last year, Liz Shutt, policy director at University Alliance, claimed that “We need to develop skills in interaction with business and in preparing students for the work world.” This is in line with the Government’s productivity plan, Fixing the Foundations3, which also cited the need for universities to contribute more to economic growth by building better and more direct links with industry.

The second issue is tuition fees. Put simply, the introduction of a student-payer system for attending university has had the consequence of focusing the minds of students far more on whether the course they do is likely to lead them to employment and how well that employment will pay. For instance, the UK Graduate Careers Survey 20154 found that the number of students who began researching their career options by the end of the first year was 48% – the highest they had ever recorded. Another indicator of the shift in attitudes is shown by the fact that degrees which tend to be associated with higher income careers, such as business and administrative studies and science-based subjects have, according to HESA5, grown hugely in popularity in recent years.

1 www.gwu.edu/~erpapers/documents/articles/goodcitizenship.cfm

2 www.economistinsights.com/sites/default/files/EIU-Ricoh Future Work - laid out report_0.pdf

3 www.gov.uk/government/publications/fixing-the-foundations-creating-a-more-prosperous-nation

4 www.highfliers.co.uk/download/2015/survey_release/Release2015.pdf

5 www.hesa.ac.uk/content/view/34844

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None of this is to take away from the important point that education is a good in itself, even where it doesn’t necessarily lead to a directly associated career. Nevertheless, universities need to be realistic and recognise that the twin pressures of the call to improve productivity and employability cannot be ignored.

This being the case, here are a couple of important questions: if your university is being called on to improve productivity by supplying skilled graduates into the workforce, how are you ensuring that your courses align with the needs of the workforce? Or to look at the picture from a slightly different angle, if your university is being called on to improve student employability, how much emphasis are you placing on the need to direct them to sustainable careers?

Our aim is to provide some workable suggestions to these questions. In the following two sections, we will be concentrating on the question of productivity, firstly from a regional perspective, and then in terms of the national economy. In the two sections that follow, we’ll be turning to the question of employability, firstly asking how universities can provide students with better information in order to make better choices, and secondly by turning to the issue of transferrable skills (which incidentally applies just as much to the “education for education sake” approach as it does to the “education for careers sake” approach). Then in the summary we’ll tie all these issues together to show how through the use of good market intelligence, your university can improve productivity and employability, and so better achieve the overarching goal of improving lives.

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We can summarise these two issues in two words: Productivity and Employability. Universities are being expected to make a greater contribution to productivity by aligning more with the needs of industry and the economy. At the same time, they are also being expected to improve the employability level of their graduates, with this expectation coming not just from the Government, but also from the students themselves. The issues of productivity and employability are in reality two sides of the same coin. The university that establishes better connections with industry and takes steps to align its curriculum with the needs of the economy, is likely to be the university with the highest rates of employability in graduate jobs. Likewise, the university that takes steps to increase student employability, is also likely to be the university that contributes most effectively to productivity.

Jamie MackayEmsi – Business Development Manager for Higher Educationjamie.mackay@economicmodelling.co.uk

Contributing to Regional Productivity

If universities are being expected by the Government and employers to contribute more effectively to increasing economic productivity, a good question to throw back to them is this: Which economy are you talking about? Such a question will probably elicit a rather quizzical expression, followed by the answer, “Well the British economy of course.” Yet the problem with this approach is immediately obvious. The British economy is clearly very broad, and so how could a university in, say, the North East begin to provide solutions which are anything other than equally broad and – as will often be the case – way off the mark?

Here’s a typical example. Last year the Royal Academy of Engineering1 (RAE) suggested we would need more than a million new engineers and technicians by 2020, and that this would require a doubling of the current number of annual engineering graduates and apprentices. However, this is a very broad statement and says nothing about what type of engineers are needed, nor about where they are going to be needed (as an aside, our data found this million figure to be hugely inflated2, and we estimate total engineering openings to be around a quarter of this amount).

In reality, there is no such thing as “the British economy”, as such, but simply a number of smaller and often very different local and regional economies which are aggregated together to form “the British economy”. For instance, the demands and priorities in the North East are generally vastly different than those in London. If we are to impact on productivity, rather than painting with the kind of broad brush which says we need X number of graduates in Y occupation, we need to be far more specific and find out what type of graduates are needed, in what numbers, and in which area.

What this suggests is that for a university to thrive in helping to increase productivity, the most effective way to do this is to look first and foremost to its own back yard, seeking to understand the economic conditions, needs and priorities in its own region, in order to then provide a supply of graduates that meets those needs and demands.

At this point, we would anticipate a good objection. Some might question the wisdom of concentrating on increasing productivity in the university region, since it is surely the case that people come to university from all over the country and then disperse all over the country after graduating. “How would it be of benefit to concentrate on increasing productivity in our own region if most graduates won’t end up working there?”

The simple answer to this question is that most graduates do end up in the same region that they studied in. Research carried out last year by the Higher Education Careers Service Unit (HECSU) – Loyals, Stayers, Returners and Incomers: Graduate migration patterns3 – identified four different types of student, according to where they come from and where they end up after university. These are:

Incomers – Those who work in a region in which they neither studied nor were domiciled

Returners – Those who study outside their home region, and then return to that region to work after graduating

Stayers – Those who study outside their home region and then stay in that region to work

Loyals – Graduates who go to university in the region where they live, and who are working in that same region six months after completing their degree

1 www.independent.co.uk/news/uk/home-news/uk-needs-over-one-million-new-engineers-and-technicians-says-royal-

academy-of-engineering-10334994.html

2 www.economicmodelling.co.uk/2015/09/29/productivity-and-the-knowledge-economy-part-2-the-problem-of-inadequate-supply

3 www.hecsu.ac.uk/assets/assets/documents/hecsu_graduate_migration_report_january_15.pdf6

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The report then went on to show these four cohorts across the 12 government regions of the UK:

As you can see, with the exception of London, the East, and the South East, in all other regions the number of students that end up working in the same region in which they studied six months after graduating (the Loyals and the Stayers) is above 50% (the average across all regions is 62.66%).

What are the implications of this? Well, if most students end up working in the area in which they studied, universities find themselves in a unique position of being able to really advance the prosperity of their region by ensuring that they are training students in the knowledge and skills that are actually needed there. Put another way, if a sizeable proportion of students that go through an institution will go on to employment in the same area, doesn’t this present a huge opportunity for universities to shape their curriculum to the needs of that region, and so play a big part in driving growth there?

Undoubtedly it does, but this begs the question of how they go about it. The answer is to tap into regional Labour Market Intelligence in order to establish what the real needs for graduate employment are in the area. For example, a university in the North East might begin by running a report on the expected demand for graduate openings in the region over the next five years:

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%NE

8.2%15.7%13.7%62.3%

NW8.6%

20.3%12.2%58.9%

Yorks10.9%25.0%18.3%45.9%

E.Mids14.9%29.5%15.2%40.4%

W.Mids13.9%31.1%9.7%

45.4%

East21.5%40.5%6.6%

31.4%

London35.6%23.0%12.4%28.9%

SE20.7%32.6%10.5%36.1%

SW16.2%29.6%13.9%40.4%

Wales7.4%

15.6%12.2%64.8%

Scotland5.1%4.4%6.2%

84.3%

N.Ireland1.4%

16.4%0.5%

81.7%

IncomersReturnersStayersLoyals

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(NB. our data drills down well below the regional level to County/Unitary Authority and even Local Authority level, and so the same exercise can be done for those sub-geographies within the broad Government Office Region).

Of course it could be that the university doesn’t currently run courses that tally to any of these occupations. What then? One solution would be to respond to the demand by widening the course portfolio to include such degrees. Another response might be to look at the institution’s current portfolio and use the data to uncover if and what the demand is like for occupations related to these courses. In the example below we have pulled the data for graduate engineering occupations in the South West:

Top 10 Graduate Occupations in the North East in Terms of Annual Openings 2015-2020

Nurses 1,949

Medical practitioners 742

Primary and nursery education teaching professionals 683

Sales accounts and business development managers 625

Secondary education teaching professionals 498

Financial managers and directors 370

Producation managers and directors in manufacturing 345

Solicitors 334

Chartered and certified accountants 312

Business and financial project management professionals 295

Top Graduate Engineering Occupations in the South West in Terms of Annual Openings 2015-2020

320

285275

155

115 10788

Design and development

engineers

Medical engineers

Engineering professionals

n.e.c.

Civil engineers

Production and process

engineers

Electrical engineers

Electronics engineers

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As you can see, the data is telling us not just “how many engineering jobs” there are in the region, but what types of engineers are going to be needed. This information can then be fed back into curriculum planning to identify areas of over and under-supply.

In other words, by accessing data informing them on the graduate demand for occupations in their region, including specialist areas, universities can start to tailor provision that actually matches that demand with adequate supply. In addition, the data can also be used to inform on which industries are employing these occupations, which in turn opens up tremendous opportunities to engage with employers who are currently experiencing skills shortages (more on that in the next part).

All this might sound fine as far as those universities that have a high proportion of students that stay in the area after graduating, but what about those that don’t? And what about those universities that do not necessarily want to focus on their region, but prefer to have a wider influence on productivity throughout the country? We’ll be turning to this issue in the next section.

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Contributing to National Productivity

For the university that has a lower proportion of students staying in their region after graduation, or the university that prefers to have a wider influence on productivity throughout the country, as opposed to just in their region, there are essentially three approaches they might take. The first is really just business as usual; that is, continuing on the same normative model of producing a supply of graduates, without identifying the demand. Does this model really help increase productivity? Not really, since under this model there is no way of knowing whether the supply of graduates going into the workplace is really what is needed. In fact, we can go further and assert that since there are clear skills gaps at graduate level, this model is not effective.

A better approach would be to look at demand for certain occupations across the national economy and to tailor course provision accordingly. So for instance, a university with an engineering department might identify the nationwide demand for related occupations throughout the country and tailor their course portfolio accordingly. However, whilst this approach is more likely to meet employer demand than the first, it is only marginally so. There may well be a demand for chemical engineers, but where is this demand? Without knowing this, the model still resembles something of a scattergun approach, far from the precision approach that is needed if we are to see real impacts on productivity.

We want to suggest a third model; one which we believe is far more precise and far more likely to have a real impact on productivity since it uses data to link universities with skills specialisms to industries across the country that are in need of those skills.

To take a hypothetical example, think of a university which offers degrees in Forestry. They may have links with local companies involved in the forestry and logging sector, but how about the rest of the country? Using LMI for the whole of the country, we can begin by quickly identifying where the major hotspots in the country are for this industry (NB. This sector is made up of four sub-industries, which are Silviculture and other forestry activities; Logging; Gathering of wild growing non-wood products; Support services to forestry):

Number of People Employed in the Forestry and Logging Industry in 2015

Scotland South East Wales East of England

South West East Midlands

West Midlands

Yorks & Humber

North West London North East

3,872

245337399

535563732

1,348

1,871

2,5892,747

South East

Scotland

Wales

West Midlands

North East

London

Yorks & Humber

East Midlands

East of England

North West

South West

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Growth and Decline in the Forestry and Logging Industry in 2015

The data can also identify which areas of the country are likely to see the most growth over the next few years. In this instance it is the South East, which is set to see around 383 new jobs created in the sector between 2015 and 2020:

By digging deeper into the data – down to the local authority level – we can even begin to get a more detailed view of which sub-geographies within the South East are set to see growth:

South East 383

Scotland 244

Wales 220

West Midlands 11

North East 3

London -4

Yorks & Humber -31

East Midlands -58

East of England -108

North West -108

South West -186

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This approach can be highly useful in terms of identifying industry needs and growth which are connected with the university’s course portfolio. But what makes this exercise even more useful is going on to identify the local employers in those growth areas. For instance, in the case of the Forestry industry in the South East, the biggest three employers are Tilhill Forestry Limited, The Tropical Forest Trust, and Euroforest Limited (this information is taken from Equifax data, which we have linked to all our industry data in our Analyst1 tool, allowing users to identify employers for any industry, along with contact details).

By taking this approach, any university can quickly and simply identify demand in those industries that are connected with course provision, for any part of the country. In addition, they can identify the employers in those industries, which can give rise to tremendous opportunities for linking with those companies to become an ongoing supplier of talent. This approach has obvious ramifications for increased productivity, as well as for increasing employability.

But there is more. Using granular data gives universities the opportunity to consolidate and strengthen their existing course portfolio in ways that can lead to increased productivity, and it also affords opportunities to diversify to include new degrees, or perhaps Higher/Degree Apprenticeships, either in areas that they have not yet explored at all, or in areas related to existing courses.

For instance, sticking with the Forestry industry, the data can be used to identify the occupations that this sector employs. The following table shows the Top 10 graduate positions within the industry in Britain:

This shows some of the other occupational requirements of the Forestry industry, outside the starting point of a degree in Forestry. So if a university has taken the approach described above, they can take this a step further by identifying other graduate needs within the same industry. This can then be used to inform their course portfolio to include degrees and/or other forms of provision such as Higher/Degree Apprenticeships that relate to other in-demand skills in the sector.

The current supply-led approach adopted by the majority of universities is unlikely to impact positively on productivity. A generalised demand-led approach will not get us much further. However, the approach we have set out above, where a university uses highly specific data to identify industries, employers and occupations that are related to their current course portfolio, or to identify possible areas of diversification, could well have a dramatic impact on productivity, not to mention the other side of the coin, employability. In the next part of this series we’ll look at employability in more detail.

Occupation Employed in Industry Group

(2015)

Employed in Industry Group

(2020)

Median Hourly Earnings

Conservation professionals 511 516 £16.30

Human resource managers and directors 221 221 £23.83

Biological scientists and biochemists 194 206 £18.87

Management consultants and business analysts 94 83 £21.00

Financial managers and directors 93 100 £29.19

Functional managers and directors n.e.c. 76 82 £24.47

Chartered and certified accountants 47 49 £19.84

Environment professionals 42 45 £17.12

IT project and programme managers 35 39 £24.19

Business and financial project management professionals 33 33 £22.49

1 www.economicmodelling.co.uk/services/analyst12

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Getting Objective About Employability

So far we have seen how universities, by taking a more methodical approach, can improve their contribution to productivity, both regionally and nationally. However, as we have pointed out previously, productivity is really only one side of the coin, the other being employability. But what is actually meant by employability? In his 2006 study, Learning and Employability1, Professor Mantz Yorke defined it as:

“A set of achievements – skills, understandings and personal attributes – that make graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community and the economy.”

He went on to say that:

“‘Employability’ refers to a graduate’s achievements and his/her potential to obtain a ‘graduate job’, and should not be confused with the actual acquisition of a ‘graduate job’ (which is subject to influences in the environment, a major influence being the state of the economy).”

We would agree with this, but would want to add something we believe to be vital. In theory, the more skills, understandings and personal attributes a person has, the more likely they are to be sought after by employers, although as Professor Yorke pointed out, this comes with the caveat that such a person is by no means guaranteed a graduate job. However, what if there was a way for someone to increase their employability not just by the skills and knowledge they learn, but also by basing their decisions of what to learn on a more realistic assessment of the labour market?

To take an illustration, Anthony and Karla live in the same region, and both intend not only to go to university in that region, but also hope to stay after graduating. Anthony does Biochemistry, but after graduating realises that there are no jobs for Biochemists in the region. Karla, on the other hand, would like to do Biochemistry, but after researching labour market demand for graduate positions in this field in the region sees that the demand for Biochemists is falling, whereas the demand for another occupation that interests her – Dentistry – is likely to rise significantly over the next few years. So instead of enrolling in Biochemistry, she instead chooses Dentistry (BDS), and when she qualifies five years later finds that there are a number of local dental practices in her area that are looking to employ.

That’s a simplistic illustration, of course, but which one is the most employable? Well in the sense of skills, understanding and attributes, they might well both be equally employable. However, whilst Anthony is faced with a choice between looking for work in a different field than he studied in, or moving into a different region where the demand for Biochemists is higher, Karla, who has taken the time to research labour market demand, is able to walk into the position she has been studying for straight away. In other words, subjectively both may well be equally employable, but Karla has actually made herself objectively more employable by aligning the skills, understanding and attributes she learns to what is most likely to lead to a sustainable career.

Students increasingly understand this, even if they don’t necessarily yet have the tools to make the kind of decision Karla made. For instance, according to the UK Graduate Careers Survey 20152, the graduating class of 2015 – the first to pay the £9,000 tuition fees – was more career- focused than previous cohorts of graduates. The Accenture Strategy 2015 UK University Graduate Employment Study3 also confirmed that graduates were more focused on career prospects and anxious to pursue a graduate-level job.

1 www.employability.ed.ac.uk/documents/Staff/HEA-Employability_in_HE(Is,IsNot).pdf

2 www.highfliers.co.uk/download/2015/graduate_market/GMReport15.pdf

3 www.accenture.com/gb-en/insight-uk-university-graduation-research.aspx13

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Another pointer to this attitude shift is to look at which degrees are the most popular. Whilst humanities and arts degrees have been declining in recent years, according to HESA1, degrees which are more associated with higher incomes, such as business and administrative studies and science-based subjects, have increased. This shift is clearly being driven by the student recognition that since they are going to come out of university with debts of over £30,000, they need to give themselves the best chance of finding employment.

However, at present this approach is very much based on assumptions rather than actual knowledge of labour market demand. Students are choosing such degrees because the careers which are related to them tend to pay well. Yet if the demand for related occupations is actually falling, would studying in this area actually improve a person’s employability any more than if they had chosen to study something else? This is not to say that someone doing a degree such as business and administrative studies won’t find work, even if demand for related careers is falling, but in such a scenario it would mean that the degree they chose in order to make themselves more employable may be of no more use to them than the degrees they ruled out as being less likely to lead to a sustainable career.To achieve the objective part of employability mentioned above, students need access to objective information about the labour market they are thinking of entering. Interestingly, the kind of information that can help them make informed choices to enhance their employability is essentially the same sort of Market Intelligence that we demonstrated before when discussing productivity.

Let’s just take an illustration. The data below shows the forecasted change in demand for Biological scientists and Biochemists from 2015-2020 at the County/Unitary Authority Level. We have included the five counties with the highest level of growth at the top in orange, and the five counties with the highest level of decline at the bottom in red:

Biological scientists and biochemists – Top and Bottom 5 in Terms of Job Change at County Level from 2015-2020

Cambridgeshire CC 323

Inner London – East 210

Inner London – West 127

North Yorkshire CC 94

Glasgow City 79

West Sussex -18

Perth & Kinross and Stirling -18

Outer London – South -19

South and West Derbyshire -25

Kent CC -39

1 www.hesa.ac.uk/content/view/348414

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How could this sort of information be used to help students become more employable? Packaged in a “student-friendly” way, it can be used to help students understand the trends of the occupation they are thinking of studying for, which in turn can help them to think through whether training for that position is necessarily a good idea. In the case above, someone in North Yorkshire who wanted to study Biochemistry and remain in the area after graduating would be encouraged by this data, whereas someone in Kent might decide it is better to look at other options. Out of interest, the graph below shows our forecast for the Top 10 highest growing graduate positions in Kent over the next five years, and so demonstrates how someone in that area might begin to make alternative choices more likely to lead them into a related, sustainable career:

As stated above, this sort of information would need to be packaged together to make it more “student friendly”, which is something we have done with our Career Coach1 tool, incorporating not just labour market demand, but also information on salaries, job postings, links to relevant courses provided by the university, and also similar careers.

This last point – the links to similar careers – is especially important. Labour market demand can and does change, and it is vital that someone studying in a particular field is aware how their achievements – the skills, understandings and personal attributes mentioned by Professor Mantz Yorke – relate to other occupations and careers. This is what we’ll be turning to in more detail in the next section.

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Top 10 Highest Growth Graduate Occupations in Kent 2015-2020

1 www.economicmodelling.co.uk/services/career-coach15

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Employability & Transferrable Skills

Using Market Intelligence to improve objective employability is all very well, but what if a student graduates and there are no jobs in the field they studied in? Or what if they have studied in a field that doesn’t necessarily relate directly to a particular career or occupation? Where does objective employability fit into this?

In the previous section, we gave the illustration of Anthony and Karla, two young people who live in the same region and intend to go to university in that region. Karla started off wanting to do Biochemistry, but changed her mind and did Dentistry, after researching demand for graduate positions. Anthony did Biochemistry, but after graduating found out there are no jobs for Biochemists in the region. So Karla ended up getting a job in her field of study, whereas Anthony didn’t. What are his options? Does he simply look for any graduate position he can find? Or failing that any job he can find? Or is there a better solution?

The answer is yes there is a better solution, and it lies in tapping into transferrable skills. In the US, there is a system known as O*NET, which is a database ranking the knowledge and skills needed for any occupation. Emsi have adapted this for the UK labour market, and we have done so in such a way that allows comparison of the knowledge and skills required in one occupation with those required in any other occupation. What this means is that we can find out which occupations are most similar in terms of knowledge and skills, and also what the knowledge and skills gaps are.

The regional graph on page 14 showed that of the numbers employed as Biological scientists and biochemists between 2015 and 2020, the lowest demand is set to be in Kent. We suggested there that someone thinking of going to university to do biochemistry, and then staying in the Kent region afterwards, might be better off first looking at occupational demand in the area to see where the jobs are set to be. But what if – like Anthony – they have done Biochemistry only to find that there are no jobs? This is where the idea of transferable skills comes in.

Top 10 closest fit occupations to Biologoical scientists and biochemists in Kent, including expected job growth/decline between 2015 and 2020

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The graph above uses O*NET data to pick out the Top 10 nearest fit occupations to Biological scientists and biochemists, in terms of skillsets and knowledgebase, with the closest on the left (Research and development managers). Not only this, but the graph also uses our data to show the demand for each of these occupations between 2015 and 2020.

This sort of intelligence has obvious benefits both at the front end of a person’s student journey – when they are thinking of what they might like to study – and at the back end, when it comes to graduating and they are applying for jobs. At the front end, such intelligence can inform them of alternative career choices that may have more demand from employers than their initial choice. At the back end, it can inform them what similar occupations they might be able to apply for if they cannot get a job in an occupation directly related to their field of study.

But there’s more. The O*Net data allows us to dig deeper to compare the knowledge required in one occupation with another. So for instance, someone who had graduated in Biochemistry, only to find that there are no Biological scientist and biochemists jobs available in their region, might want to do a comparison of what they have learnt with some of the most compatible occupations to find out where their knowledge gaps are. So for example, if we compare the knowledge base for Biological scientist and biochemist with the closest compatible occupation, Research and development manager, we find the following:

The orange parts are the gaps between knowledge needed as a Biological scientist or biochemist, and that which is needed as a Research and development manager. Where this information is invaluable is in making a graduate who cannot get a job in their field of study aware of where they might upskill in order to be able to move into a related career. Imagine taking these insights into a job interview!

In the final part of this report, we will attempt to draw all the strands of this series together, to summarise how market intelligence can be used by Higher Education institutions to Improve Lives.

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In Summary

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We began by asking what is the purpose of education, and our answer was that it is ultimately about improving lives. Whether education is seen primarily as a method of passing a body of knowledge on from one generation to the next, or equipping people to be able to think critically and analytically, or equipping people with the skills and knowledge that will help them to succeed in the world of work, the common denominator behind all of these ideas is the thought of elevating people to a better level of knowledge and understanding.

Education which passes on meaningful knowledge, understanding and skills is therefore a good in itself, and nothing we have written is intended to undermine that principle. Nevertheless, what we have attempted to do is recognise that there is a noticeable and widening gap between the needs of local economies and what universities are teaching, and a widening gap between the needs of employers and the knowledge and skills being learned by students. These two issues – productivity and employability – are two sides of the same coin.

We went on to look at how universities might better close the productivity gap through the use of market intelligence. We began by looking at how this can be done from a regional perspective, showing how regional data can be used to gain a better understanding of graduate demand in their area, which can then be used to tailor a course portfolio which better supplies that need. We then went on to look at the productivity issue from a national perspective, showing how market intelligence can be used by universities to identify the location of industries around the country that are closely relate to degrees within their course portfolio. Furthermore, the data can also be used to identify the employers in these industries, giving universities the opportunity to forge better links.

We then tackled the other side of the coin – employability. We began by showing that whereas employability is often seen in subjective terms – the skills and attributes possessed by the graduate – there is also an objective element to it. That objective element is the knowledge of what sorts of graduate occupations are likely to be in demand, and the person in possession of this is – all other things being equal – more likely to find a job that is related to their field of study than someone who isn’t. We then went on to ask the question, “what happens if there are no jobs in the graduate’s field of study?” Our answer lay in the identifying of transferrable skills. By using data which compares one job to another, graduates can firstly see which other occupations they might want to look for outside that which is directly related to their field of study, and secondly they can better understand where their knowledge and skills gaps are in looking for other occupations.

None of this is to say that market intelligence is the solution to the productivity and employability problems. Following our suggestions will not make these problems disappear. However, if universities are serious about tackling these issues, good market intelligence must undoubtedly be part of the answer. Good data will help universities better understand their region’s needs, and the needs of industries in other parts of the country that align with their course portfolio. Good data will also help universities enable their students to be more aware of the real opportunities out there and of the most similar opportunities should they not be able to find work in their field of study.

It is by better understanding the regional and national economy that universities can close both the productivity and employability gaps, and therefore achieve the overarching goal of improving lives.

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To find out more about how Emsi can help your university close the productivity and employability gaps, contact us at:

Email: info@economicmodelling.co.uk Phone: 07720 641 651

Web: www.economicmodelling.co.uk Blog: www.economicmodelling.co.uk/blog

Twitter: @EMSI_UK