Data-driven diversity and inclusion (D&I)

Data-driven diversity and inclusion (D&I) adoption by US companies is a growing trend. There are many reasons for this, including:

• The business case for D&I is clear. Companies with more diverse workforces are more profitable, innovative, and better able to attract and retain top talent.
• Data can help companies identify and address unconscious bias. Unconscious bias is a major barrier to D&I, and data can help companies identify and address it in their hiring, promotion, and other practices.
• Data can help companies track their progress on D&I goals. This is essential for accountability and for making sure that D&I efforts are having a real impact.

There are many ways that companies can use data to improve their D&I efforts. Here are a few examples to use data:

• Identify areas where your workforce is not diverse. Include topics such as gender, race, ethnicity, age, or disability.
• Track your progress on D&I goals. Examples: the number of women in leadership positions or the number of employees with disabilities
• Identify unconscious bias in your hiring, promotion, and other practices, e.g., the use of biased language in job postings or the underrepresentation of certain groups in certain departments.
• Develop and implement D&I initiatives. This could include things like unconscious bias training or mentoring programs for underrepresented groups.

Data-driven D&I adoption is a complex and challenging process, but it is essential for companies that want to create a more inclusive and equitable workplace.

Data-driven diversity and inclusion

This was the topic of an HR.com webcast. Data and artificial intelligence are trending topics for human resources professionals. Diversity & Inclusion (D&I) has been a workplace hot topic for a number of years.

Organizational impacts of D&I:

• Organizations with inclusive cultures are twice as likely to meet or exceed financial targets than those without (source: Deloitte)
• 21% of companies that have greater gender diversity are more likely to have higher profitability (source: McKinsey)

Measurable Diversity (examples)

• ratio of male to female employees
• ratio of white to non-white or mixed ethnicity
• percent of leadership team is female
• percent of board of directors is ethnically diverse

Workplace Inclusion

• Why diverse candidates opt out of the recruitment cycle
• Why high performing diverse employees leave after 2 year

Facets of diversity to consider include: gender identity, race/ethnicity, sexual orientation, age, educational background, family or caregiver status, native language, physical abilities, and veteran status.

Read more:

Visier's Big Book of People Analytics: D&I