Financial and professional services toolkit

For employers

Measurement

Part one: Measuring socio-economic diversity

Why data matters

Measuring the socio-economic background of your employees and potential recruits is the critical first step. It helps you know what needs to be done in order to improve the socio-economic diversity and inclusion in your organisation.

We’ve consulted with dozens of academic experts, think tanks, charities and employers to produce this simple guide to the most important information you need to collect.

Asking your workforce, apprentices and applicants just three key questions will give you a firm basis on which to develop an informed strategy for improving social mobility.

What to ask

Whether you are just starting out or you’ve had a social mobility strategy for years, make sure you ask job applicants, apprentices and your workforce this one key question:

What to ask?

What was the occupation of your main household earner when you were about aged 14?

  • Modern professional & traditional professional occupations such as: teacher, nurse, physiotherapist, social worker, musician, police officer (sergeant or above), software designer, accountant, solicitor, medical practitioner, scientist, civil / mechanical engineer.
  • Senior, middle or junior managers or administrators such as: finance manager, chief executive, large business owner, office manager, retail manager, bank manager, restaurant manager, warehouse manager.
  • Clerical and intermediate occupations such as: secretary, personal assistant, call centre agent, clerical worker, nursery nurse.
  • Technical and craft occupations such as: motor mechanic, plumber, printer, electrician, gardener, train driver.
  • Routine, semi-routine manual and service occupations such as: postal worker, machine operative, security guard, caretaker, farm worker, catering assistant, sales assistant, HGV driver, cleaner, porter, packer, labourer, waiter/waitress, bar staff.
  • Long-term unemployed (claimed Jobseeker’s Allowance or earlier unemployment benefit for more than a year).
  • Small business owners who employed less than 25 people such as: corner shop owners, small plumbing companies, retail shop owner, single restaurant or cafe owner, taxi owner, garage owner.
  • Other such as: retired, this question does not apply to me, I don’t know.
  • I prefer not to say.

  • Why ask?

    This question is the best measure to assess someone’s socio-economic background. Not only that but it’s easy to understand, it gets the highest response rates in testing, and it’s applicable to those from all ages and from all countries. It really can’t be simpler!

    What did we change?

    Old versions of this question had multiple follow-up questions that helped improve its accuracy. We worked with a group of experts to simplify this question and change the response categories to make it fit-for-purpose for employers looking for a one-question measure of socio-economic diversity. If you’re already asking the older four-part version, rest assured, there is no need to update your question. Consider using this one-part version for supplementary staff surveys, where you may lack the space for the full version.

    Click here for more details.

    How to analyze?

    Report socio-economic background in three groups, following this guide:

    • Professional backgrounds – modern professional & traditional occupations; senior or junior managers or administrators.
    • Intermediate backgrounds – clerical and intermediate occupations; small business owners.
    • Lower socio-economic backgrounds – technical and craft occupations; routine, semi-routine manual and service occupations; long-term unemployed.
    • Exclude – other; I prefer not to say.

    You’ve got your data. Now what?

    Review the proportion of applicants and staff members from each socio-economic background – is there equal or close to equal representation from each group? If not, which is the dominant socio-economic group?

    Compare your results to the following national benchmarks for the entire workforce:*

    Parental occupation at age 14

    37%
    Professional
    24%
    Intermediate
    39%
    Working class
    Find out how these benchmarks were calculated

    *Benchmarks based on entire workforce in England

    Industry benchmarks can also be found on our microsite for the financial and professional services, public sector, creative sector, SMEs and retail sectors.

How to lead best practice?
Invite the companies in your supply chain to ask this simple question of their workforce, too!

If you are already implementing diversity and inclusion initiatives, or want to get a fast-track to ‘optimising’ status, it’s easy to go to the next level by asking two further simple questions:

What to ask?

Which type of school did you attend for the most time between the ages of 11 and 16?

  • A state-run or state-funded school
  • Independent or fee-paying school
  • Independent or fee-paying school, where I received a means tested bursary covering 90% or more of the total cost of attending throughout my time there
  • Attended school outside the UK
  • I don’t know
  • I prefer not to say

Why ask?

This measure shows extreme economic and cultural advantage. Our joint research with the Sutton Trust, Elitist Britain, shows how private school attendees are overrepresented in many of the UK’s top jobs. Plus, many employers at the forefront of this agenda have collected this measure for years. Use this longitudinal data to see how your business is performing over time.1

What did we change?

A new category for those who received a full bursary to attend independent schools.

How to analyze?

Simply look at the percentage of respondents who went to an independent school (without a complete bursary) compared to all others, excluding those who say ‘I don’t know,’ ‘Prefer not to say’ and ‘Attended school outside the UK’.

How to interpret?

Review the proportion of applicants and staff members who attended an independent or fee-paying school – what is the size of the group compared to the national benchmark?

Type of school attended at age 11–16

7.5% Independent schools

Other information

Our partners at the Social Mobility Foundation suggest advanced employers (and law firms, who are required by the SRA) include ‘Selective state school’ and ‘Non-selective state school’ in the response categories for this question to get an even clearer picture of the type of school respondents attended. These give you additional nuance to understand your workforce but it is important to note they are not substitutes for measuring social background. Always compare this data alongside parental occupation (question 1).

1 Our partners at the Social Mobility Foundation additionally suggest advanced employers (and law firms, who are required to by the SRA) include ‘Selective state school’ and ‘Non-selective state school’ in the response categories for this question to get an even clearer picture of the type of school respondents attended.

What to ask?

If you finished school after 1980, were you eligible for free school meals at any point during your school years?

  • Yes
  • No
  • Not applicable (finished school before 1980 or went to school overseas)
  • I don’t know
  • I prefer not to say

Why ask?

This is a measure of extreme economic disadvantage. The poorest 15% of the population receive free school meals. It’s easy to understand and many firms have been tracking it for years, giving you longitudinal data.

What did we change?

Nothing.

How to analyze?

Link ‘yes’ responses to economic disadvantage and exclude those who said ‘not applicable,’ ‘I don’t know’ or ‘prefer not to say’.

How to interpret?

Review the proportions of applicants and staff members who were eligible for free school meals – what is the size of the group compared to the national benchmark? It’s important to note this question isn’t a substitute for measuring social background and should always be reviewed alongside parental occupation (question 1).

Free school meal eligibility

15% Pupils at state-funded schools


If you have a graduate scheme, ask this additional question to your graduate hires only:

What to ask?

Did either of your parents attend university and gain a degree (e.g. BA/BSc or equivalent) by the time you were 18?

  • No, neither of my parents attended university
  • Yes, one or both of my parents attended university
  • Do not know / not sure
  • I prefer not to say

Why ask?

Attending university gives a nuanced form of cultural advantage, as organisational cultures favour attendees. Being the ‘first in family’ to attend signals a potential lack of support to navigate university and entry into the graduate workforce. This can help you understand the experiences and needs of your graduate hires.

What did we change?

We replaced a previous question on parental qualifications with this one. Find out why here.

How to interpret?

Review the proportions of new graduate hires who said ‘no’ and are thus first in family to attend university and compare it to the national benchmark. Remember this is not a measure of social background and should always be interpreted alongside the parental occupation question (question 1).

67%
of graduates are first in family to attend uni

Part two: Build trust to drive up response rates

Your data will only be as good as the number of people who answer the questions. Here are some suggestions about how to engage your workforce in the data gathering process.


Reassurance on data protection

It is important to reassure about data storage and use so that applicants and staff members feel comfortable to respond to surveys.

Be clear on:

  • whether individuals can be identified from the data they provide
  • whether information will be stored separately from personal details and in line with data protection rules
  • who will have access to the information
  • whether they might be contacted as a result of the information they have given, for example, to share materials about support related to a protected characteristic (though this is generally discouraged)
  • what your anonymity threshold is (the general rule of thumb is you should not look at groups with fewer than 10 responses)


Getting buy-in

Response rates are likely to rise if the data gathering is presented in the context of a vision for creating a more socially diverse and inclusive workplace, which provides opportunities for all.

Begin to take action to embed the issue of socio-economic diversity and inclusion into your organisation. For example, get senior leaders to act as role models by writing blogs and emails to communicate the importance of data, or share examples of how data has already highlighted opportunities for positive change.

View the toolkit for more suggestions and check out how HMRC drove up response rates in this case study.

Part three: Progression

Why progression matters

Social mobility isn’t just about who gets in, it’s also about who gets on. Talented individuals from lower socio-economic backgrounds are often overlooked when it comes to moving up. By looking at progression you can ensure that talent does not get wasted on the rungs of your organisation.


How to look at it

By using the results of question 1 (on parental occupation), you can see if there is equal representation of socio-economic groups at each grade or seniority level. Follow these steps:


  • 1.Breakdown your current workforce: Split occupations in your organisation by grade or seniority level (e.g. managing director vs. associates etc.).
  • 2.Analyse the data: Use Excel or your HR software to see what percentage of people at each grade or seniority level are in the three socio-economic background groups (working class, intermediate and professional). Ensure you consider anonymity – the ‘rule of thumb’ is not to analyse results below 10, so group levels together if needed (e.g. analyse all C-suite leaders in together if there are fewer than 10 of them).
  • 3.Interpret the results: Is there equal or close to equal representation of socio-economic backgrounds at each grade or seniority level? Is there a group that dominates a certain occupation or grade level? Does your data have a ‘cliff edge’ effect, where those from lower socio-economic backgrounds suddenly fall off, or a ‘pyramid’ effect, where they slowly fall off as you go higher in seniority?

How this helps

An organisation that wants to get the best out of its workforce, and that is committed to socio-economic diversity and inclusion is one where an employee’s start in life does not limit what they can achieve.

Understanding where those from lower socio-economic backgrounds stop progressing will help you identify the barriers that are limiting upward mobility in your organisation, and help you introduce measures to improve social representation and inclusion across all levels of seniority.


How to benchmark

There is no national benchmark for progression, because every organisation is structured differently. However, we can look at the industry’s performance by looking at the class pay gap and the proportion of those from working class backgrounds in professional roles. Neither of these are perfect, but they do show the broad strokes gaps in pay and progression by socio-economic background. Financial services can also consider work from our partners at the Bridge Group and City of London who found it takes those from lower socio-economic backgrounds 25% longer to progress through grades.

Distribution of the professional workforce by socio-economic background across sub‑sectors 1

Distribution of the higher managerial and professional workforce by NS-SEC category of the main wage earner when respondent was 14.

1 Sample sizes in the legal sector for those from working class backgrounds in professional roles fell below 100, which is the threshold for reliable statistical reporting on a population. As such, we have not reported the legal sector in this graphic.


PFS: Socio-economic background and weekly pay in the FPS industry
Median weekly pay* for those from different socio-economic backgrounds

* Median weekly pay for individuals with higher socio-economic background based on the LFS, against modelled median weekly pay for individuals from intermediate and lower socio-economic background who are otherwise similar (in terms of characteristics included in the model).

Part four: Metrics to measure the success of apprenticeships and training

Apprentices and training can be a powerful tool for social mobility. But are they? Our research into apprenticeships has found that too many people assume apprenticeships are working for social mobility, even when they’re not. We also find that adults from lower socio-economic backgrounds routinely get overlooked for training opportunities.

Don’t fall into this trap – take these steps to measure who is actually getting access to apprenticeships and training. Only then can you ensure that such initiatives are actually driving socio-economic diversity in your organisation.


  • 1.Get the overall picture. Start by asking a) apprenticeship applicants b) existing apprentices and c) those receiving substantive training opportunities the same question(s) as in step one, above. Analyse your overall apprenticeship and training makeup as you would with your workforce (laid out in section one, above).
  • 2.Access by level. Look at the spread of socio-economic groups throughout the apprenticeship levels you offer (and, if applicable, your developmental training opportunities, excluding mandatory and required trainings). Are there certain apprenticeships or training offers that are over or under-represented by socio-economic status?
    • a.Why? Generally, apprentices from low socio-economic backgrounds get ‘stuck’ at lower levels (Level 2 and 3) while more privileged apprentices take advantage of subsidised degree level apprenticeships (Levels 6 and 7). Our research also finds this balance persists for older apprentices (those above 25+). We also know that adults from low socio-economic backgrounds at every occupation level miss out on training more generally, compared to their more privileged peers.
    • b.Target: Comparable proportions of socio-economic groups at each apprenticeship level.
  • 3.Completion rates. Look at the percentage of learners who have completed apprenticeships by socio-economic background.
    • a.Understand why. Our research shows lower socio-economic apprentices often drop out at higher rates, often because they are unsupported, face a workforce that isn’t inclusive or face financial difficulty.
    • b.Target: Comparable rates across all socio-economic groups.
  • 4.Progression. After training is done… then what? After all, training and apprenticeships are designed to help your workers improve their performance and subsequently advance up the ladder. Use your workforce data to look at who receives a promotion or goes onto a higher level of apprenticeship within a set period of time after they are done with their training.

1. Do not count mandatory occupational health and safety training here, as it does not tend to link to career progression and could skew your data
 
Make your data the foundation of good strategy

Want to dive deeper?
Click here to see what we did, why we did it, and what the limitations of this approach are.

See how other leading organisations are making changes

National benchmarks

Parental occupation at age 14

37%
Professional
24%
Intermediate
39%
Working class
Find out how these benchmarks were calculated

Type of school attended at age 11–16

7.5% Independent schools


Free school meal eligibility

15% Pupils at state-funded schools


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Created and endorsed by the Social Mobility Commission and these partners

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