Diversity Data: The challenges of data collection and developing a culture of self-reporting

With the anticipation of mandatory ethnicity pay gap reporting, and an increased focus on race prompted by the Black Lives Matter movement, Financial Services firms have been reviewing and expanding their data collection and reporting practices. However, good intentions are being hampered by a lack of availability of data. PwC found that only 25% of the firms they surveyed have sufficient data to calculate their ethnicity pay gap¹. Data on other characteristics such as disability, socio-economic background, faith, caring responsibilities, sexual orientation, gender identity and neurodiversity give employers further understanding of the diversity of their workforce, but this data is often lacking or non-existent.

Improved diversity and inclusion leads to better diversity of thought and therefore better business outcomes. Having the data available to analyse diversity is the crucial first step to being able to target improvements in workforce diversity and inclusion. Here we explore some of the barriers to collecting diversity data and how these can be addressed, highlighting examples of best practice.

“Data collection is crucial to improving workforce diversity and inclusion”

Legal concerns are not barriers to action

Many firms report GDPR and legal concerns as a barrier to collecting and holding data. Data such as ethnicity, sexual orientation and disability are all considered sensitive according to GDPR which means that the way the information is used or stored has stricter requirements compared to, for example, gender. These barriers are not insurmountable, many firms already ask employees to voluntarily self-disclose this information as outlined in the GDPR guidance. This is true for the UK at least. Firms with international HR systems face a further challenge as data protection laws differ from country to country. Global HR teams must consult with local lawyers to ensure that they are not breaching any laws by applying the same data collection policies from one country to another.

Building trust and encouraging disclosure

Once employees are given the option to report their personal data, the next challenge is encouraging them to do so. Meaningful data analysis is difficult with low response rates and this then impacts the ability to measure improvements in diversity and inclusion. The CIPD found that the overwhelming reason for poor data disclosure related to employees’ trust in their employers².

Employees are often concerned with how their data will be used; employers must provide reassurances about the specific purpose data will be used for. It should also be clear how and where the data will be stored. Transparency around data collection, performance management and recruitment strategies is necessary if employers want the best engagement from employees.

Employees must be reassured that their data is confidential. Lesbian, gay and bisexual staff may have particular concerns if they are not out at work. Companies must make it explicit how data will be secured and that it will not be personally identifiable. Clydesdale Bank run an anonymous staff diversity survey which includes questions on sexual orientation. It is made clear to all employees that the data is confidential and anonymous before they complete the survey. Whilst some of the data in the survey is analysed at individual business unit level, sexual orientation data is only published at UK level to avoid identifying any individuals³.

“Employees are often concerned with how their data will be used”

Employees may also be concerned about how the data collected will be used. Research by Scope found one reason disabled people do not disclose their disability at work is fear it may limit their employment and progression opportunities⁴. If data collection is accompanied by a visible offer of support for disabled employees, then this reassures staff of the benefits of disclosing their information. If employers offer both anonymous data capture and formal data capture through HR systems, they may be able to capture some data about employees who are not ready to disclose information formally⁵. Firms can still act on anonymous data and use it to improve inclusivity.

Firms can also use employee resource groups to encourage staff to self-identify on HR systems, either as part of a data collection cycle or in reminders throughout the year. Employees could be asked to ensure their personal data (such as address and telephone number) are up to date in the system and then be prompted to input additional personal details. Senior leadership in companies can also advocate for employees to provide data by making staff aware of the data they are sharing themselves, helping to give employees confidence that their data will be used positively.

Disclosure rates vary across the sector, however those firms with higher disclosure rates have often had a long-term programme in place of target setting, reporting, leadership and employee engagement that has helped to increase disclosure over time and this reporting transparency has improved the trust with their employees that the data shared has a purpose and a value to the organization and the individual.

“At M&G we believe that data collection and reporting is at the heart of ensuring our Diversity and Inclusion strategy is having the desired effect on us becoming an exceptional place to work. We include all aspects of self-identification for colleagues around the globe including, where legally allowed, gender/gender identity, sexual orientation, disability, ethnicity/nationality, age, and military service. This level of data collection and reporting allow us to ensure our current colleagues feel recognized, that there is no bias in our talent management processes and that future colleagues know they can bring their whole self to work as a valued member of the M&G family.”

Mark McLane, Head of Diversity, Inclusion and Wellbeing at M&G

Can systems cope?

Before employers start asking for additional data from employees, they need to ensure their HR systems are equipped to capture, store and manage the data. Legacy HR systems may need upgrading to be able to capture a wider variety of data. To make inputting this data easier, there may need to be improved user experience design. These upgrades will have associated costs but difficulties in inputting data may be a barrier for busy employees so systems should be as intuitive as possible.

Expanding data collection

Firms which already have good processes embedded for data collection will find it easier to expand the data they are asking for from employees. If individuals are used to regularly providing data in pulse surveys or as part of their annual compliance training, then they will be more likely to provide additional data. Firms who do not collect any data currently may find resistance if they immediately move to asking employees about their ethnicity, sexual orientation, gender identity, parent’s education and neurodiversity, all in one go. The firms with good data collection have likely implemented this over a designed period of time. Smaller firms may find it easier to communicate with employees on the need for collecting this data so may be able to implement bigger changes faster. Larger firms may want to consider which data they think will be most important and start with improving collection of these data points, staggering their data collection. Lloyds Banking Group is one firm with significant data collection which allows them to publish the gender split of its workforce at Board, executive committee and direct reports, senior managers and colleague levels. In addition, it publishes the percentage of its workforce who are from a BAME background at colleague, manager and senior manager grade and percentage of the workforce who disclose a disability or identify as LGBT. This data will have taken several years to collect but is an example of what is possible.

PwC recommend an 80%+ disclosure rate for analysing data; however, some insight can still be gained with disclosure rates above 60%⁶. Where response rates are low, data can be supplemented with focus groups or by concentrating analysis on specific areas with higher disclosure. Firms should be cautious of basing decisions on low quality or incomplete data. In large companies, statistical analysis is easier with slightly lower response rates as the higher total number of responses improves the sample. In small companies it is hard to extrapolate from a small source so higher response rates are necessary.

Sector wide collaboration on D&I

The Financial Services Skills Commission has identified improvements in data measurement, analysis, and reporting as one of its ambitions for improving diversity, inclusion and progression⁷. Having access to detailed data will allow companies to understand issues with recruitment, attrition, promotions and any bias in the company’s people processes. Analysis of this data can therefore offer far reaching insights and have real financial impact. If businesses can discern where they have the highest rates of attrition and why, they can implement changes and retain skilled talent. Businesses can ensure that their recruitment process means they have access to the widest talent pool possible, reducing the risk they will not have access to the skills needed. Analytics can often shake up long held beliefs about the reasons people leave roles or where the best talent comes from. Having the best quality and broadest data increases the power of data analytics.

“Access to data will help companies understand issues with recruitment, attrition, promotions and bias in processes”

Case study: Zurich
Zurich, as part of its diversity and inclusion strategy, has increased its public pay gap reporting to include race, LGBT+ and disability alongside gender. By making these pay gaps public, Zurich is accountable to its stakeholders.

Case study: Barclays
When applying for jobs at Barclays, applicants are asked their sexual orientation. This data moves with applicants onto the HR system when hired. Not only does this increase disclosure rates by adding another point where employees are asked for data, it allows Barclays to analyse this data in relation to recruitment practices.

Case study: Financial Services Skills Commission members
A survey of our members found that a number of firms are already reporting their ethnicity data externally, with other firms looking to do so in the following 12 months. Firms are also publicly setting targets for their BAME representation alongside this data.

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