Labour market information: a user guide

Careers professionals and those working in graduate recruitment often use labour market information (LMI) to boost their knowledge and inform their work - but delving into the data can be daunting if you're unfamiliar with it or new to the sector

This guide is intended to provide an overview of what LMI is, who it's for, how to make best use of it and avoid the potential pitfalls, and a glossary of key terms.

What is graduate LMI?

Graduate labour market information refers to the current economic and employment landscape as it relates to graduates. Typically, it includes the latest information on factors such as graduate destinations, average graduate starting salaries and trends in graduate recruitment patterns - as well as anything that may have an impact on these factors (for example, the effect of artificial intelligence on graduate recruitment practices, technological change, or changes in government policy).

LMI generally comes in two forms:

• Quantitative information - numerical information, usually the result of rigorous research.
• Qualitative information - typically extracted from interviews and focus groups. This is sometimes referred to as 'soft LMI' and cannot be considered to be statistically representative of the larger population.

Such information is usually collected by both government and private organisations (including academic and research establishments, employer groups, and trade unions). As a result, a wealth of reliable and comparable LMI is available at the national and regional levels, although it is much harder to source at the local level.

Once the quantitative and/or qualitative information gathered in these ways has been analysed and interpreted - perhaps for presentation to an audience - it is often described instead as labour market intelligence. For simplicity this guide will refer to labour market information throughout.

Who is labour market information for?

Graduate LMI is useful for anyone wanting to understand the composition of the labour market and its health. It is particularly valuable for careers professionals who need a strong knowledge of the economy to help students and graduates make an informed decision about their future career.

Sharing information with graduates about industries and occupations helps them consider which professions are suitable for them, what additional qualifications they need to acquire, how much competition there is for roles and whether they need to develop any new and existing skills or gain experience. Regional data also enables students to plan their job search effectively as they will have a greater awareness of the opportunities available in their local area, and if their chosen profession is in demand in another region they can consider relocating for work.

Furthermore, data on skills shortages can be used by careers professionals to design workshops which will provide graduates with the skills required by employers which can help increase their employability prospects.

Employers can also benefit from using graduate LMI to inform their recruitment campaigns. Knowing how many graduates studied each subject, what grades they achieved and which occupations and industries they enter gives employers a better idea of who to target their vacancies at. Demographic data for each region and subject is essential for organisations that are looking to diversify their workforce so they can adjust their targets where appropriate to ensure that different groups of people are fairly represented. It's also important to look at migration data as graduates aren't necessarily highly mobile, so employers need to see who is coming into the region and whether they need to do more to attract graduates and help them relocate.

How careers professionals can use graduate LMI

1. Identify in-demand skills and occupations

It is likely that students and graduates seeking information/advice on the labour market will be particularly interested in discovering the skills and occupations that are - or will be - in most demand. Because of this, it is useful to stay up to date with the latest information regarding both professions with hard-to-fill vacancies, as well as the skills that are most needed across the UK. Although it will always be helpful to stay on top of the latest trends, remember to give advice on a case-by-case basis - for this reason, it is also important to have an understanding of the most recent regional data, for example.

2. Identify job prospects in a particular area

Graduate Outcomes data has revealed that the majority of graduates either studied and found employment within their home region, or returned home to find employment after moving to another area for study. Consequently, students and graduates are likely to be interested in the job prospects within their specific locales. For instance, they may be interested in the industries that are hiring in their respective city or region, as well as the average salaries they can expect to receive. It is important that careers advisers know about the relevant LMI within the region in which their particular institutions are located.

It is likely that students looking for advice will often be unaware of specific LMI concerning their hometowns (e.g. the jobs that are available there, cost of living etc.). Therefore it is important to determine the extent of their knowledge about the labour market - that way you can be aware of gaps in knowledge that you can fill. A student may have preconceived notions about the opportunities available to them and it is vital that careers professionals make them aware of all their potential prospects once they leave higher education.

3. Identify employers' requirements for graduate hires

Many students seek advice prior to graduation and some of them will have a clear career path in mind. They may need advice on the requirements they need to meet to compete in the job market - for example, this might include minimum degree classifications or specific professional qualifications for certain roles. Other students may be unsure of what they want to do and, even if they do, in many cases they will not be aware of every opportunity made available to them by their degree, especially when it comes to jobs that don't require particular degree subjects or classifications. All of this information falls under the definition of LMI.

4. Make students aware of graduate schemes and internships

Internships and graduate schemes are a great way for students and graduates to gain the experience and training necessary to help them excel in the professional world. Although some will be aware of these opportunities, many who are seeking advice will not be as informed. Details of what schemes are available, when time of the year recruitment takes place, and what the assessment process look like can be invaluable to their chances of success.

How employers can use graduate LMI

1. Expand your knowledge of graduate salaries

To entice jobseekers employers will need to offer a competitive salary, or risk losing graduates to rivals. HESA's Graduate Outcomes survey asks graduates how much they are earning fifteen months after graduation, and this data can be broken down by industry, occupation and region to help employers set a starting salary. For example, an engineering firm in the North West can look at the data to see that engineering professionals in their region earned £31,269 on average (according to the latest data) and then assess how much they can afford to pay based on this figure. They can also look at the national average (£28,731) to see how their region's salary compares to the average for all UK engineering employers. The full dataset is not publicly available without purchase, but the top-level findings can be accessed freely.

It should be noted that salary figures will sometimes differ depending on the sample size. HESA's Graduate Outcomes survey asks all recent graduates about their salary fifteen months after graduation, but the Institute of Student Employers (ISE) collect data by asking their members - typically larger employers - how much they offer graduates. This explains why the average graduate starting salary reported by the ISE (£35,170) is higher than the Graduate Outcomes figure (£28,726).

 2. Use location data to improve campaigns

 To find out where a region's talent supply comes from employers can use Graduate Outcomes data to track the percentage of graduates that come to their region for work and discover how many local graduates stay in the area after leaving university. For example, an employer in the West Midlands can see that 74% of UK domiciled, first-degree graduates working there were originally from the region. Incomers were typically from neighbouring regions such as the East Midlands, the South East and the North West. They can then use these insights to plan recruitment campaigns and narrow down the areas they would like to target. It can also help to manage expectations and challenge the belief that graduates are highly mobile and are always willing to migrate for employment.

They can also see from the data that there is no brain drain of graduates to London, with only 9% of university leavers from the West Midlands moving there for work, so employers don't need to worry about losing talent to the capital to quite the extent that they otherwise might.

3. Explore skills shortages

If you're struggling to fill your vacancies and find applicants with the required skills it could be a result of occupational shortages, so it's worth keeping an eye on the list of professions that are hard to fill. Skills shortage data can help employers distinguish whether recruitment difficulties are a regional or national issue. If it's specific to their region they can look at targeting graduates from further afield.

The Employer Skills Survey includes a list of skills that employers report as hard to obtain from applicants and employers can use this data to estimate the training needs of new employees. For instance, 36.2% of hiring professionals reported that applicants lacked the ability to manage their own time and prioritise tasks, so running time management workshops for new and existing employees could be a potential solution. Also, if they lack specialist knowledge or skills, employers could consider reducing the salary and training candidates instead. Apprenticeships are another possible option. It's useful for employers to share this data when working with universities so course designers know what skills are in demand.

4. Make use of subject-level data

Knowing which students gravitate towards each industry and occupation helps employers understand which graduates they are likely to attract, and they can estimate what type of skills and experience potential hires will have. For example, if a company is trying to recruit a marketing associate professional they can use the most recent Graduate Outcomes data to see that the most common degrees held by graduates in these roles were marketing, business studies, management studies, and business and management. Then, when it comes to writing their marketing associate professional job adverts and shortlisting CVs the employer can suggest that graduates from these subject disciplines will be suitable candidates.

Subject-level data is useful for measuring talent supply. Once you've identified which subjects you want to target you can find the number of students enrolled onto those courses and compare the figures with previous years to anticipate any future supply and demand issues.

5. Understand how graduates find jobs

Data on where graduates found their jobs can help employers prioritise the most effective platforms to advertise their vacancies on. For instance, as part of the Early Careers Survey 2024, Prospects found that job websites/apps and social media/networking sites were among the most popular resources used by graduates to find employment, so if you're looking to target graduates from any discipline it would be wise to use these channels.

However, it's been shown that graduate job-hunting methods do differ by occupation, subject, sex, ethnicity and region, so if you are aiming to develop a more representative workforce it is worthwhile looking at more granular data to determine how you can reach certain groups of graduates.

6. Inform your diversity and inclusion strategy

A diverse workforce should have a graduate intake that is broadly representative of the student population where possible. According to data from HESA, around three fifths (58%) of 2021/22 graduates were female, 16% were from an ethnic minority background, and 14% had a disability.

However, some employers may struggle to reflect these statistics in their workforce data due to the under/over-representation of certain groups within each subject discipline. For example, a company that is aiming to attract a high proportion of female applicants for their software developer vacancies may struggle to achieve this goal as only 22% of graduates from a computer science background were female according to the latest data.

The Office for Students (OfS) has a convenient tool which can be used to find the percentage of students studying each subject by ethnicity, disability, sex and educational disadvantage (POLAR 4).1 You can use this subject-level data to measure how small or large the diversity challenge is within your organisation by comparing the percentage of students by ethnicity and gender against the total for all students. 

7. Identify hiring trends in the sector

Do you wonder what other businesses are doing to attract graduates? Are you using the most effective selection tools to select candidates? The answers to these questions and more can be found in reports such as the ISE's annual Student Recruitment Survey, which is an invaluable resource for those interested in student recruitment strategies.

You can compare your selection procedures with the data in that report, which contains the methods used by other organisations to see whether you are utilising the most popular hiring techniques. The data on their effectiveness is subjective, but it can be useful if you're looking to try new ideas, perhaps to see whether it's worth taking a risk and changing up the hiring process. For example, an employer that is considering using psychometric tests can see in the 2022 report that, although respondents found that psychometric assessments were most effective at in the first stage of the selection process, they were much less effective in the final stage. Employers can use this information to consider additional ways to determine a candidates suitability for a role if they choose this option.

If you're wondering what core requirements you should set for your vacancies you can find lists of the minimum requirements set for graduate hires and the percentage of companies that used each one to help inform your decision. It's also worthwhile to consider whether it's advantageous to follow the trend and set a 2.1 degree as a benchmark, or set a lower standard to widen your applicant pool. This may be beneficial if your industry/occupation is suffering from acute shortages of skills and workers.

What to avoid when using LMI

Unreliable information

LMI is considered unreliable if reported findings are not replicable when the data used to ascertain them is re-analysed using an identical method. The utilisation of unreliable LMI can result in misinformation not only being used to make recruitment decisions, but also being disseminated to graduates looking for an accurate representation of the graduate labour market in order to make informed decisions about their potential careers post-graduation. This can be avoided by assessing who has produced the information in question and determining if they are trustworthy and impartial. It is also useful to see if similar data is available from an alternative source, as this will help to achieve a balanced view.

Invalid information

LMI is considered invalid if it doesn't measure what it is meant to in a specific situation, causing it to be of little use. As an example, if a student is seeking information on the labour market in their home town, providing data that treats the UK as a unified labour market will be of little or no use to them. To ensure that LMI being used measures and represents what you are intending to discover, you must determine:

• How the data has been collected - e.g. has it been collected in a scientific manner?
• How it has been aggregated and classified - as this can be done using different systems that can have implications for the comparability and robustness of the LMI being viewed.
• Whether it's up to date - the graduate labour market is subject to change over time and making use of outdated information can give a false impression.
• Whether it's fit for purpose - e.g. is it disaggregated to the appropriate level or appropriate for the individual needs of the user.2

Out of date information

It is vital that LMI being used is the most up to date data available as it is subject to change over time. Not only have industrial classifications changed, but geographical boundaries are also likely to do the same. To determine if the LMI being used is up-to-date you must think about:

• When the research was carried out?
• What time period does the data relate to?
• When it was published?
• The date of the next release
• If more recent research exists which either supports or contradicts the data being used?3

Being too general

Because every individual will have differing aspirations and circumstances (e.g. degree type, degree classification, work experience etc.) it is important that LMI provided on an individual basis isn't too general. In each case, it is vital that any information provided is assessed with the individual in mind - meaning the usefulness of that information must be determined on an individual basis, a practice that can help prevent the dissemination of irrelevant information.

Therefore, it is important to ask each individual a set of questions to determine what LMI they can make the most use of, such as:

• Where would he or she like to work? (e.g. which region, city etc.)
• What are your career ambitions?
• How much do you expect to earn?

Once you've gained a good idea of an individual's aspirations and expectations, it makes the process of seeking out the appropriate LMI more efficient.

Using unrepresentative data

A representative sample refers to one that is as representative as possible of the population from which it is drawn. For instance, if a population is 60% female and 40% male, a sample which reflects this can be considered representative. On the other hand, a sample that is 70% male and 30% female would be unrepresentative of the population in question. A representative sample is more likely to yield findings that are a reflection of the wider population, meaning that findings will be generalisable to the population from which the sample was selected (e.g. graduates across the UK fifteen months after graduation).

Furthermore, when making generalisations (even with a representative sample), it is important to remember that we cannot make inferences beyond the population from which the sample was selected. Therefore, any findings that are found in the UK context are not generalisable beyond it as graduate labour markets will vary between countries.

Assuming that the national/regional picture reflects the local one

A great deal of reliable and comparable LMI exists at both the national and regional level, but this is much harder to find at the local level. Multiple factors have an effect on local labour markets (e.g. a locales specific geography, demography etc.) that can cause them to vary quite drastically from the national or even regional picture. For instance, skills shortages that may be particularly acute in a certain locale may not be so acute in nationally. Therefore, it can be misleading to provide LMI to a student that wishes to stay within their city/town based on an analysis of national or regional data.

Relying on averages

Remember to treat averages as what they are - the 'mean' or total distribution of values divided by the number of values. Averages are useful, however, they hide the level of variation that exists within any dataset as extremely large or small values can skew the mean. For instance, salaries can vary greatly in professional occupations - therefore, the average pay for a specific occupation may represent a figure that is either higher or lower than the typical salary that a graduate going into that occupation can expect. With this in mind, it is important to make students aware of this when providing advice. This way they will be able to make informed decisions and temper expectations.

Making false comparisons

Comparing your data with previous releases is appealing and can reveal some interesting trends, but it's important to make sure that the methodology hasn't altered as this could make any findings invalid. For example, HESA's Graduate Outcomes data cannot be compared with data from its predecessor Destinations of Leavers from Higher Education survey, as the way the data was collected differs considerably. Despite the fact that both surveys aim to capture graduate activity after leaving university, the differing reference points (fifteen months for Graduate Outcomes and six months for DLHE) makes it impossible to compare both sets of data.

Glossary of LMI terms

APS – the Annual Population Survey is a continuous survey of UK households to gather social and socio-economic data at local level.

DLHE – the Destinations of Leavers from Higher Education survey tracked graduate activity six months after leaving university until it was replaced in 2018 by the Graduate Outcomes survey.

Graduate Outcomes - this is the UK's largest annual survey of graduates and captures their destinations and perspectives 15 months after graduation. It is carried out by the Higher Education Statistics Authority (HESA), which like Prospects Luminate is part of Jisc.

Hard-to-fill vacancies - these are vacancies that employers struggle to fill for any reason. This is a subjective measure as the employer judges how hard the vacancy was to fill.

HECoS - the Higher Education Classification of Subjects system is used to code higher education courses based on their modules and content.

JACS - Joint Academic Coding of Subjects was a system used to identify the subject area of UK higher education courses. It was replaced by HECoS in 2019.

LEO - Longitudinal Education Outcomes data looks at how much graduates from different institutions and courses earn one, three, five or ten years after graduating.

LFS - the Labour Force Survey is the largest household study of the UK population's employment activity to gather data on the country's employment and unemployment rates.

Non-professional level job - these jobs are defined using the Office for National Statistics' Standard Occupational Classification system. Roles in SOC groups 4-9 are considered to be 'non-professional level'.

POLAR (Participation of Local Areas) - this classification system places local areas into quintiles based on the rate of young people in higher education.

Professional-level job - a professional-level role is defined using the Office for National Statistics' Standard Occupational Classification system. Roles in SOC groups 1-3 are considered to be 'professional level'.

SIC - the Standard Industrial Classification system classifies the industries that UK businesses belong to.  

Skill-shortage vacancies - these are vacancies that employers find hard to fill specifically because applicants lacked relevant skills, qualifications or experience.

SOC - the Standard Occupational Classification system groups UK professions into classes.

Working age population - individuals aged 15-64 fall into this group.

Notes

1. Student characteristics data: Population data, Office for Students.
2. Quality standards: assessing labour market information for practice, Connexions Kent and Warwick History of Employment Research, 2008.
3. Ibid.