In the world of business, you’re likely used to looking at numbers to help you make decisions. Data is used to guide company decisions, goals and strategies on a daily basis. You study the numbers to improve operations, expand offerings and connect with your customers, but when it comes to diversity, equity, and inclusion (DEI) a peculiar trend emerges. Although companies have accepted the importance of DEI, most aren’t using their tried-and-true data-driven practices in this area. To drive meaningful change, talking about the importance of diversity—while important—isn’t enough. Companies genuinely committed to overcoming challenges need to use data to identify issues, establish benchmarks and track progress.
This also requires a focus on the correct data. Many diversity metrics are viewed as a headcount—how many women, people of colour or individuals from underrepresented groups are employed at the company? How many are in leadership roles? These are outcome metrics, and can serve as a crucial gauge for showing us that a problem exists.
Outcome metrics are a great start—if there are no underrepresented groups in your company, a problem exists—but they don’t look at the root cause of the problem. If a company is only recording outcome metrics, they’ll likely find that there isn’t a lot of change from month to month or year to year. Unless there are large staffing changes within the company, the outcome data numbers are unlikely to change wildly.
To truly advance DEI efforts, we should also be looking at process metrics. These dive deeper into the employee-management processes including hiring, evaluation, promotion and executive sponsorship. Instead of tallying the total number of underrepresented people in leadership, process data looks at how often people from underrepresented groups are being promoted through the corporate hierarchy or whether there are salary differences between genders in comparable roles.
When it comes to hiring, process data can highlight problems in four areas: recruitment, résumé review, interviewing and the making and negotiating of offers. In each case, if you identify a problem, there’s a different fix. For example, if you find that there isn’t much diversity in your new hire pool, the solution may be additional outreach in new communities or placing job ads on job boards focused on DEI. To correct for bias in the hiring process, specialized training for your interviewers can help make sure that all applicants are being asked the same questions to review their skills and qualifications.
Process data can also help identify and address bias—such as tightrope biases— in an organization. This type of bias rewards white men for being authoritative and ambitious but often penalizes members of other groups for behaving in the same way. A 2020 study found that tech company workers who “took charge” tended to receive the highest ratings on performance evaluations—but only if they were men.
By taking a closer look at your company’s performance reviews, you may find data highlighting a bias you didn’t know existed. Once you know that there are biases in your hiring or promotion processes, you can start to find solutions.
Don’t limit diversity data to mere headcounts of underrepresented groups. Outcome metrics are essential, but only reveal the existence of a problem. Process metrics, on the other hand, pinpoint issues within employee-management processes such as hiring, evaluation, promotion and executive sponsorship. They provide actionable insights into where to direct efforts for meaningful change.