Diversity and data are, separately, two hot topics in HR but can the latter inform the former to drive better outcomes for all employees?
In HR, data and diversity increasingly go hand-in-hand. Often with a habit of making headlines. ‘Only one third of UK firms have ethnically diverse boardrooms.’ ‘Only 15% of CEO roles are held by women.’ ‘The UK gender pay gap is 17.3%.’ ‘Only three per cent of Silicon Valley workers are black.’ In part, it’s because this topline data provides a very easy way of understanding where a given entity – be it country, industry or business – is regards their diversity efforts, which groups they need to improve representation of, and where in the business, or employee lifespan, improvements need to be made. (As well, of course, providing pesky journalists a headline to showcase just what firms should be doing!)
Diversity and inclusion is unfortunately often seen as a ‘soft’ subject in many companies, uninformed by hard data or analytics
To provide ‘big picture’ clarity is one of the reasons why Kelly Metcalf, Head of Diversity, Inclusion and Wellbeing at Fujitsu, utilises data in her diversity efforts. She tells HR Grapevine that data has allowed the firm to pinpoint where it was failing regards diversity, allowing it to create an HR strategy to rectify issues. She says: “Data plays a huge role in our inclusion and diversity strategy at Fujitsu. Our biggest measure of the progress we are making in diversity and inclusion – given the requirement to publish this externally – is our annual gender pay gap. Like the majority of organisations in the UK and the technology sector, we have a gender pay gap favouring men. Understanding what this gender pay gap is and the data behind it gives us an objective measure of the reasons for the gap and helps to inform our gender diversity action plan – a set of activities focused on achieving gender equality and eradicating the pay gap.”
Metcalf also believes that whereas D&I might have traditionally been viewed of as a ‘soft subject’, it is increasingly being viewed as business critical and, as such, is being measured properly. She adds: “I am passionate about ensuring we maintain and improve on this data-focused approach. In my view, diversity and inclusion is unfortunately often seen as a ‘soft’ subject in many companies, uninformed by hard data or analytics. But in fact, data is such an integral part of our diversity and inclusion strategy within Fujitsu; it helps us to form an objective understanding of our colleagues, it commands the attention of senior leadership and helps us to deliver genuine results.” (This thinking dovetails with increased understanding of, not only diversity as a key driver of business success, but data too. In last month’s magazine, in an exclusive interview, Josh Bersin told HR Grapevine that HR had to get increasingly savvy to the data in order to drive it’s own success and the success of the business. In fact, research from Thompson Online Benefits found that almost half of firms now have a people analytics teams to help drive success.
Yet, although Metcalf extols the benefits of data, knowing where to measure and get data can be difficult though. Payroll data is an obvious place to start, to showcase the makeup of your firm, as well as drilling down into the company hierarchy to see where diversity issues might be hidden. Noel Thomas, Co-Founder and Director at CA3 and Eli, branding and onboarding experts, also adds that onboarding is a place where data can easily be gleaned – and more qualitative metrics, such as engagement, can be measured. “Onboarding is the perfect time to develop and embed a more inclusive working culture – it’s also the perfect place to generate data and MI that can support your D&I agenda,” he says.
From the data we collect as part of our regular engagement surveys, we’re able to determine how the experience of our colleagues differs based on where they are nationally and internationally
Thomas adds: “By tracking and analysing engagement levels, ratings, survey results and MI of specific groups during onboarding, organisations can start to build a real understanding of how included your new employees feel, as well as how much value they themselves place in D&I. If you then filter that MI, to focus on specific departments for instance, HR are then able to pinpoint groups that are succeeding and those that might need more support or training (whether that be the new employees themselves, their line managers or teams).”
When we start to break down demographic groups, many companies struggle
This approach, which takes into account measuring how employees feel, seems to be an important facet for Fujitsu too, ensuring that any diversity or inclusivity data it collects isn’t just decided upon by leadership teams. Furthermore, by continually measuring, Fujitsu can then get feedback and insight into groups it might have missed by a purely top-down approach. “From the data we collect as part of our regular engagement surveys, we’re able to determine how the experience of our colleagues differs based on where they are nationally and internationally, which then informs how we adapt our ongoing approach in helping people from different regions. For the first time, we also collected data on carers within this survey and with this, we are now able to start understanding the unique needs and experiences of carers within Fujitsu, together with the more traditionally recognised forms of diversity as referenced above,” she adds.
Whilst this all sounds good, there is a caveat. According to academics Katie Wullert, Shannon Gilmartin and Caroline Simard, publishing a joint article in Harvard Business Review last year, diversity data can sometimes hide diversity issues. “An organisation may be able to tell a clear story about how women in general are faring, or may be able to discuss the experiences of people of colour broadly, but what about Asian women compared to Black women, or Hispanic men compared to white men? When we start to break down demographic groups, many companies struggle,” they wrote. Often, the academics added, when companies start off on a data journey they revert to broad categories to help structure their diversity initiatives. The implication for HR is that actually they need not to settle, and much like Thomas and Metcalf advocate, engage their workforce, way before implementation stage, to pinpoint what needs to improve and how included individuals feel.
How can HR rectify bad diversity data?
Stanford University’s Wullert, Gilmartin and Simard are aware that sometimes data can hide the real diversity and inclusion issues at a firm. To combat this, they recommend three core HR behaviours: