Hard data critical to achieving equality and diversity goals

The old business saying goes that you can’t manage what you can’t or don’t measure. That applies especially to areas like equality, diversity and inclusion where progress has often been impeded by a lack of hard data.

“Data is critical to being able to measure progress in terms of both diversity and inclusion,” says Glenn Gillard, a risk reputation partner with Deloitte.

“At the start of any initiative, taking a baseline measure of the current status enables an organisation to assess whether the effort and investment put into diversity and inclusion is having an impact. This in turn supports a business case for further investment.”

According to Gillard, there are a number of different data points that companies can use as a starting point, such as hiring, attrition and headcount at different grades to get a picture of their diversity landscape.

“Companies often hold data around gender, age, nationality and in some cases disability, so these measures can be evaluated to see if there are different hiring or attrition rates by gender or age, for example,” he explains.

“Hiring can be assessed against gender or age data to see whether the recruitment campaign or selection process may be biased towards one group or another,” he says.

Promotion

Cal Muckley, professor of operational risk in banking and finance at UCD College of Business, agrees. “It strikes me that statistical modelling techniques are very useful for informing promotion decisions,” he says.

“If you find that you are overly promoting candidates from a particular gender you can ask questions about it. You could set up model to find the traits shared by the people who did get promoted and then set up programmes to develop those traits in others to help them achieve promotions.”

Identifying the characteristics that get people promoted is just the start, however. “The question is if we can encourage people to develop those traits instead of implementing gender quotas,” says Prof Muckley.

“That would be a more sophisticated step. If it turns out people already possess those traits that could be a sign of some sort of bias at work.”

Deloitte is adopting more sophisticated approaches to break down processes and compare data at various points, as well as attempting to collect richer data. “We have started to embed a comprehensive voluntary D&I questionnaire into our recruitment processes to enable us to monitor the diversity of the candidates we are attracting across a range of measures such as gender, ethnicity, faith, disability,” says Gillard.

“This enables us to measure whether our selection processes have any unconscious biases that might lead to a skew in who is offered a role, and to create a targeted campaign if we wish to attract more people from an underrepresented group. We can then measure the success of that campaign based on the data we have collected. “

Gender pay gap

Gillard gives some simple examples of how organisations can use data to improve their equality, diversity and inclusion performance. “A company could use its payroll data to calculate its gender pay gap and ascertain if there is a significant gap between males and females. It could also look at headcount data by grade to identify a gap in the number of females relative to males at senior levels of the organisation. Further review of HR data can help assess whether this gap stems from differential hiring rates, attrition rates, promotion rates or access to key learning experiences.”

The results from this readily accessible data can be used to prompt further actions. “If the data indicates that a company hires equal numbers of males and females but that attrition of females is higher, then it should explore what data it is gathering around attrition,” says Gillard.

“Is there exit interview data, or data around flexible working or maternity leave? If an organisation doesn’t have this data, then conducting a survey or running focus groups is another way to gather it. However, without the data, the company won’t really know what the problem is that it is trying to address. It may decide to offer better paid maternity leave when the real issue is that women aren’t getting access to the right projects to prepare them for senior roles.”

Gillard concludes by arguing that going to a little bit of trouble to gather the data will be worth it in the end. “Complexity of gathering data and internal systems, GDPR and the lack of legislation can be obstacles to companies fully tracking or measuring EDI activities,” he notes.

“If companies can find ways around such roadblocks and track the right metrics it can actually help them understand the risk areas and opportunities, track the progress of initiatives and calculate return on investment.”