Join Ipsos’ Grace Tong to hear more about measuring pay equity to take action on structural and implicit bias inside an organization.
Organizations around the world are trying to solve the problem of pay inequity. Whether driven by the need to fulfill regulatory reporting requirements, attract equity-seeking talent or out of a genuine desire to promote a culture of equity, organizations are facing the challenge of accurately measuring and understanding the root cause of their pay gaps. However, few organizations have the analytical know-how to do this effectively, and even more difficulty identifying how to address closing the gaps. For many, the programs and policies contributing to inequity are often long-standing and hidden in plain sight within even the most well-intentioned organizations. The causes of inequity need to be surfaced to be corrected.
Listen in as Grace and her co-present share a case study on pay equity analysis, where predictive analytics was used to identify pay gaps within an organization, and to accurately measure the magnitude of structural and implicit bias in pay across gender, ethnicity, and the intersectionality of various identity variables. The analysis also offers organizations statistically driven insights that can help to pinpoint the root causes of inequity and recommendations on how to close the gaps related to gender and other social identities.
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