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Recap: Using workforce data to understand and improve social mobility

As an employer, data is one of the most important tools you have for understanding and improving diversity in your workplace, including social mobility. However, many employers report that collecting socio-economic data remains their biggest challenge.

In our latest masterclass we explored the importance of collecting relevant and high quality data, including practical advice such as what you should be asking, and how you should be asking for this information, how to communicate this to employees and increase response rates, and what to do with the data once you have it. 

We were joined by Tracy Garrad, CEO of AXA Health, who, alongside sharing her own personal story of social mobility, gave some great insights into why improving and collecting data on socio-economic background is beneficial for organisations, and a detailed look at AXA’s data strategy. 

If you missed it, you can watch the recording below, and read on for our recap of her top tips.


1. Better data benefits everyone 

Trying to improve social mobility benefits both your employees and your organisation. Tracy says that it just makes sense if you want to attract and retain the best talent, and be an inspiring place to work. “If you’re not getting large swathes of the population,” she says, “you’re cutting off opportunities to get the best people into your organisation.”  

There is a “battle for talent” at the moment, and “being able to spot potential from less typical sources and being able to grow your own creates massive loyalty for your organisation.”

In addition, the benefits of a diverse workforce are well understood, with many researchers including Harvard Business School and McKinsey publishing reports on the subject. Diverse teams produce better results, both in terms of risk management and financial outcomes. 

Tracy also points out that many of the actions you might take to drive forward improved socio-economic diversity within your workforce also translate into actions that pay dividends across all other diversity strands. For example, she says, “if you are thinking about e.g. literacy or numeracy tests rather than a specific qualification, you are probably also going to open up applications in terms of race, ethnicity, and disability.” By collecting better socio-economic data, you can implement strategies that benefit everyone. 


2. Show the benefit 

When AXA initially began to collect socio-economic data as part of their broader diversity data in March 2021, they found that around 40% of their employees provided their data within the first few months, but then response rates began to plateau. 

It was clear that people who felt a resonance with one of the other diversity strands were more likely to provide their data, with those who didn’t consider themselves to be from any minority group less likely to respond. 

AXA were able to see from the initial data that almost half of respondents were carers. Based on this data, they acted quickly to put together a carers’ policy and support group within the organisation, demonstrating to all employees that they really did want to use the data provided to benefit employees. Tracy explains that showing AXA had listened and learned, and were able to use their findings to improve employee experience helped to show people the value of the data, and response rates began to steadily increase.


3. Don’t go it alone

Whether you’re trying to improve your data collection, or you’re just starting to think about data for the first time, don’t forget that there are lots of resources out there to help you. 

Some of Tracy’s recommendations include the Bridge Group, and Progress Together which exists to drive this agenda forward for financial and professional services. 

She was particularly grateful for the support and input of Business in the Community, who provided tailored guidance, partnering with AXA to look at how to approach social mobility in the context of their broader inclusion strategy. We were also really pleased to hear her recommend our own ‘Let’s Talk About Class’ resources as “brilliant”!

Overall though, Tracy thinks it’s essential to just get a plan together and make a start. “There are lots of people willing to help,” she says, and “you can get great advice from attending webinars like this, but most of all just do something and do it now!” 


4. Communication is essential 

One of Tracy’s biggest learnings from improving AXA’s data collection is that the organisations who find it hardest are those who “[haven’t] put enough effort into the comms.”

Building trust is essential, she says, so it’s important that you lay out in simple language what you will and will not do with the data employees provide, as well as who will and will not have access to that data. 

At AXA, they were clear that only a very small group in the HR analytics team would see the data, and aggregated data shared with team managers to see trends in their workforce would never show below 10 employees, so they could be confident of their privacy. It was also important, Tracy points out, to reassure staff that the data they provided would never be used in decisions about progression or redundancy. Being transparent about the data use in this way helped employees to feel confident answering AXA’s questions, and improve their response rate. 

Another strategy that helped to drive up AXA’s response rate was mobilising a group of “social mobility allies group”. This encouraged people who were comfortable telling their own social mobility story to do so, helping to show that there were people of all backgrounds at each level of the company. 


5. There’s always more to be done

AXA’s journey to better data collection started with their ‘Fairer in 5’ campaign, focused on how the 7 diversity data questions (including socio-economic background) could be completed in less than 5 minutes. They initially set a target of 60% of employees sharing their data in the first year of the campaign, because, Tracy explains, 60% was the “magic number” in terms of statistical reliability. They’ve now hit a total of 63% completion, but they’re not stopping there, and have now increased their goal to 70%. 

Tracy believes that there’s still more to be done in terms of role-modelling and telling personal stories at AXA, in order to increase completion rates. “You can’t overcommunicate,” she says, “Even if each time you only catch 2 or 3 more people, that’s 2 or 3 more people where you’ve busted those myths!” 


Final thoughts 

One great question that we didn’t have time to answer live was around the SMC’s view on using self-declared social mobility data, as opposed to data on, for example, parental occupation

We wouldn’t recommend asking employees to self-declare which of the three socio-economic backgrounds they are – this is better assessed by asking the key question of parental occupation when someone was aged about 14. Research by Professor Sam Friedman at LSE highlights that people from professional, middle class backgrounds often misidentify their origins as working class. Therefore, self-declaration may not give you the most accurate picture of the socio-economic backgrounds of your workforce. You can read more about Professor Friedman’s research in this Guardian interview. 

Collecting relevant and high quality data is necessary when working to improve social mobility for a number of reasons. It allows you to analyse the full extent of the inequality within your organisation, guides your practices, measures their impact, and helps you to celebrate your successes. No matter where you are on your journey, or the type of organisation you work for, by improving the socio-economic data you collect, you will be able to implement better informed policies, and improve social mobility within your workforce. 

Tracy sums it up, saying “You get the best from people when they feel that they can be themselves. They’ll feel that they can be themselves when they can be honest about their background, when they feel like it’s not something that will be used against them, that will hold them back.”