Apprenticeships toolkit

For employers



Part one: How to measure the socio-economic background of your apprentices

Why is it important?

It’s hard to figure out where you need to concentrate your efforts if you don’t know where the barriers are. Data is an important foundation of your work because knowing the socio-economic background of your applicants and apprentices will allow you to understand where you are doing well and where you need to improve.

What question to ask?

Finding out the socio-economic background of your applicants and existing apprentices doesn’t have to be complicated, though it needs to be done in a sensitive way. You should use this simple key question:

Key question

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 occupationssuch 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.
Target: Aim for a 66% response rate.

Collect this data as an anonymous screener at the application stage for both internal and external candidates, so that you can see the distribution of socio-economic backgrounds among the people applying.

“Data has been really useful in grounding conversations and setting them up. No one can argue with that data, it’s ‘here are the facts, here’s what’s going on.’”
– Anna Morrison, Director, Amazing Apprenticeships

Tip: Offer additional guidance if this question doesn’t apply

Parental occupation is the most accurate measure available to assess socio-economic background. It is widely used and endorsed by academics because of its ability to produce a distribution of socio-economic background. However, there may be some circumstances where this question does not apply; for example, for apprentices who have grown up in foster care or have been refugees. We recommend you offer the following additional guidance:

  • encourage people to respond to the question as best as they can based on their circumstances and emphasise that it’s totally fine to use the ‘other’ or ‘prefer not to say’ option if it isn’t possible or they don’t feel comfortable answering
  • explain that the reason the question asks for ‘about age 14’ is because that is the time when most people’s parents’ or carers’ jobs have stabilised; however, it doesn’t have to be exactly 14 if it is hard to remember or there was a temporary change in occupation around that time

Part two: How to ask the question

Be sensitive about how you ask the question and ensure anonymity. This question can be very personal for people, and some might choose not to disclose for fear of stigma or negative career impact, so taking the time to build trust in the process can help increase response rates.

“I felt awkward filling in the question about my background. This was my first role, and I didn’t want to be judged.”
– apprentice workshop participant

A few things that can help with this:

  • Make sure people understand why you are asking the question and why it’s important. Communicate your vision for a more diverse and inclusive workforce, why it matters to the organisation and how you will use this data to work towards it.
  • Anonymise data when reporting results and explain to people that it will not be used for appointment or promotion decisions. Have strong data protection protocols and ensure is handled according to GDPR best practice.

  • Make sure people cannot be identified from the data by not going below the anonymity threshold of 10. If your cohort of apprentices is smaller, make sure you still collect the data at the application stage from all candidates (including internal applicants) and look at trends over time to find out whether you are attracting people from a range of backgrounds.
  • Make it clear to all staff that everyone is being asked this question, not just apprentices. This is part of a wider effort to increase socio-economic diversity and inclusion across the organisation.
  • Provide several opportunities for apprentices to answer this question. They might feel more comfortable doing so a few months into the programme or as part of their end of year review.
  • Align data collection efforts between employers and training providers to avoid duplication and ensure this is done with apprentices’ consent. Sometimes, apprentices might feel more comfortable giving this information to their training providers or even an independent charity partner (such as Multiverse or Apprentice Nation).

Part three: How to analyse your data

To understand whether particular socio-economic groups are over or under-represented in your apprenticeship programme and if these differences are related to particular stages, we recommend breaking the data down into the following categories, where applicable:


Who applies to your apprenticeship programmes (broken down by different stages, if applicable) – make sure you collect data from internal applicants as well

Why? This can help you assess your organisation’s outreach strategy and whether you are attracting the people you intended, including among internal candidates.

​Target: Proportionate to the national benchmark, unless you are purposefully trying to increase apprentices from low socio-economic backgrounds as part of a wider diversity and inclusion strategy.


Who gets an offer and starts on your programme

Why? Comparing this with the data on applications is an important indicator of how inclusive your recruitment process is (e.g. if there is a significant drop in one socio-economic group that correlates with a particular stage in the application process, this might point to a barrier).

​Target: Proportionate to the national benchmark, unless you are purposefully trying to increase apprentices from low socio-economic backgrounds as part of a wider diversity and inclusion strategy.

Overall make-up of apprentices*

Who is currently on your apprenticeship programme

Why? Before you analyse your data more granularly, you need to know the overall socio-economic make-up of your current cohort of apprentices so you can understand your baseline.

​Target: Proportionate to the national benchmark, unless you are purposefully trying to increase apprentices from low socio-economic backgrounds as part of a wider diversity and inclusion strategy.


Who is training at which levels, including degree apprenticeships

Why? More Level 2 and 3 apprenticeship places tend to be offered to people from low socio-economic backgrounds (regardless of age) compared to Level 4 upwards, which tend to be dominated by more privileged apprentices. Data can help you recognise whether you are replicating the same pattern.

​Target: Proportionate to the national benchmark, unless you are purposefully trying to increase apprentices from low socio-economic backgrounds as part of a wider diversity and inclusion strategy.

Functional Skills

Who completes the Functional Skills Qualification (FSQ)

Why? The Functional Skills requirements can be a barrier, particularly for older learners who may have struggled with these subjects in school, those with a learning disability or apprentices with a migration background. Linking the socio-economic background data to FSQ can reveal whether the support system you put in place is working to enable everyone to complete their qualification.

​Target: Comparable completion rates across all socio-economic groups within your apprenticeship programme.


Who completes the apprenticeship, including end point assessments

Why? Our research shows apprentices from lower socio-economic backgrounds tend to drop out at higher rates, often because they are unsupported, feel excluded or face financial difficulty. Use your data to find out if this is happening in your programme too.

​Target: Comparable completion rates across all socio-economic groups within your apprenticeship programme


Who receives a promotion, goes onto a higher level of training, salary or a job after they finish their apprenticeship

Why? Comparing this data within your apprentices can help you identify if there are barriers that are limiting upward mobility in your organisation. You should also look at progression for apprentices compared to general progression rates across the organisation, to see if apprenticeships are helping give people a boost, as they are designed to do.

Target: Comparable progression rates across all socio-economic groups within your apprenticeship programme.

* most important dimensions to focus on if you are just starting out