Ensuring pay equity is an emerging priority of organizations, a trend driven by Legal/Regulatory changes, pressures from activist investors and greater understanding among executives of the business value of workforce diversity. Advanced, “predictive” analytics have become central to the process of assessing pay equity and determining the policy changes and specific pay adjustments required to eliminate pay disparities in a sustainable way. Typically this involves estimation of statistical models of base and total compensation to better understand and quantify the factors that drive pay in organizations and develop “predicted pay” levels against which “actual pay” can be compared.
Join us as Haig Nalbantian and Brian Levine of Mercer will show how companies are using predictive analytics to support their Pay Equity efforts. They will focus on methodologies and tools as well as the practical considerations involved in applying predictive modeling to solve the pay equity problem. They will also show the importance of evaluating pay equity in the broader context of an organization’s underlying talent dynamics of promotion, retention and performance. They will demonstrate how advanced workforce analytics can quantify these linkages and help inform a more successful Diversity & Inclusion strategy and sustainably achieve effective pay equity.