Multiple studies have proven that the benefits of building a more inclusive and diverse workforce make an organisation more productive, enable HR to attract the right talent, and create societal benefits. A Catalyst and Harvard Business School study of Fortune 500 boardrooms found that companies with gender-inclusive teams were better at CSR efforts and contributed more to charitable funds. Companies with more women on the board statistically outperform their peers over a long period. In a survey of 1,000 respondents, the job site Glassdoor found that 67 per cent of job seekers look at workforce diversity when evaluating an offer.
We are clearly past the stage where we are still debating the benefits of a more inclusive and diverse workplace. Then why does it remain an area which has seen more lip service than actual impact?
Multiple organisations have implemented interventions to promote inclusion and diversity, but are we truly inclusive in the way we communicate as an organisation or with each other? Using data and analytics can be a ‘game changer’ here - it can help identify the deterrents of inclusion, where they exist, and provide focused and targeted interventions to address them and build an inclusive and diverse organisation.
Using a data-driven scientific approach is required to identify the addressable areas.
How HR policies are written
A large part of the employee experience is governed by HR policies and documentation. Amongst others, we should also consider taking them through a ‘bias review’ where the use of machine learning algorithms can help ensure that the language is inclusive. In our analysis of HR policy documents and communication, we have found instances of biased language in anywhere between 5-15 percent of the sentences.
How different diverse cohorts interact with each other
Analysing the interaction patterns amongst different diverse groups using ONA (Organisation Network Analysis) gives us insights into any inherent biases. The insights can be made further meaningful and actionable by understanding the patterns between diverse groups and formal organisation relationships (supervisor, peer, etc.). Instances of homophily between the same gender or other diverse groups are commonly observed and are a strong indication of an inherent bias to reach out to people of the same group.
Leaders being self-aware
Leaders play the most critical role in driving an inclusive environment and are often unaware of the unconscious biases that might result in them creating a non-inclusive environment. For instance, wanting to empathise with a working mother and offering her to not travel for a critical client meeting. The employee, who had worked tirelessly on this client and was keen to attend the meeting, feels excluded – completely inadvertently.
How daily decisions are made around people
There is immense value in comparing hiring, performance, and promotion data, engagement levels, supervisor feedback, attrition rates, compensation and rewards data, etc., for different diversity cohorts. Further analysis can help identify equity concerns around pay and career opportunities. This helps establish the connection between daily decisions and the resulting diversity outcomes or the lack of them.
Using the insights to sensitise and enable
Measuring data from different diverse groups gives us the power to dig deeper and identify areas needing sensitisation and enablement.
Dig deeper, with context
One of the most common diversity challenges we see across cohorts is their representation at senior levels. A deep dive into their interaction patterns (using ONA) would give you insights if they have a ‘weaker’ network or a ‘weaker’ relationship with their supervisor, which could have an impact on their career growth. Are the interaction patterns different from what is expected from their role?
Digging deeper will also give indications of whether the pattern is driven by the individual or the supervisor or is a systemic issue across the organisation. Using ONA analysis alongside the context of the role, team, organisation, level, formal organisation relationships, etc. can help pinpoint where the problem lies and hence who we need to sensitise.
Set enablement goals, not ‘quotas’
An example of how organisations have dealt with diversity challenges at senior levels is to ensure a certain number of promotions for these diverse groups, i.e., quotas. However, if diversity has been achieved at the cost of meritocracy, the whole purpose of inclusion is defeated.
Rather than chasing numbers, diversity goals and targets should focus on enablement and the process that will lead to the numbers. For having a more diverse top leadership, rather than putting a target on the promotion numbers, use data to guide on what will enable senior professionals to get there. Do they have mentors and the right support in the organisation or at home to enable them to work better?
Enable the leaders
Leaders would benefit from a self-discovery process to identify any behaviors they may be exhibiting that prevent them to create an inclusive environment. There are multiple scientific tests, (like the implicit association test) that are available to help leaders in this journey. The self-discovery sensitises leaders and enables them to drive “psychological safety” in their teams which can bring out an exponential impact on innovation, collaboration, and business results. Role modeling at the senior levels by members of desired diversity becomes a strong attractor for the members of that diversity to be part of the organisation.
Building an environment in our organisations where all diverse cohorts feel included with a sense of belonging is our first step in the journey. The next frontier would be embracing the diversity of mind – the cognitive and emotional diversity! Long road ahead, one step at a time…