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.
