Finding Stability in the Shifting DEI Landscape.
The Trump administration has ended the federal government’s long-standing relationship with diversity, equity and inclusion programs, including for federal contractors, subcontractors and grantees. In Executive Order No. 14173, the administration also ordered all government agencies to “combat illegal private-sector DEI preferences, mandates, policies, programs, and activities.”

For HR professionals and attorneys working on DEI and EEOC mandated affirmative action plans, this is a seismic shift. In addition, for those working on discrimination matters the recent executive order, statements by Acting Chair of the EEOC, Andrea Lucus, and the U.S. Supreme Court’s pending decision on Ames v. Ohio Department of Youth Services each point to the likely increase in cases of compensation and employment discrimination against the typically “advantaged” group in Title VII demographic characteristics. This puts companies between the proverbial rock and a hard place – damned if you do too much for any protected demographic group and damned if you do too little.

However, this webinar will show you that the tools you already use to investigate pay equity can put you in the comfy space between that rock and a hard place.

This webinar will discuss the statistical methods and explanatory variables needed to perform pay equity testing post DEI. It will review the factors discussed in the recent executive orders, mandates by the EEOC and Courts at the trial and appellate level and examine where those legal/regulatory settings are consistent with factors used in economic and statistical science. This webinar will also cover some basic aspects of the statistical method used to test for pay inequity, known as regression.

In this Webinar you will learn the following:

1. How the new executive orders and EEOC stated goals impact how pay equity analyses should be performed

2. How the “merit-based” hiring standards stated as the focus of the EEOC and executive orders will influence explanatory factors

3. Whether there are sets of explanatory factors that work in all legal settings

4. What the statistical standards are that define a valid set of explanatory variables, such as a t-test and P-value

5. How to choose a set of explanatory variables that will last over several years and perhaps election  cycles

Advanced Analytical Consulting Group (AACG) has PhD labor economics experts who testify in court for and against the Department of Labor. AACG is also the sole distributor of EquityPath software, which is used by corporations, government agencies and law firms to analyze pay equity. AACG also has statistics and computer experts who can implement these tests for/with you on secure servers at AACG, in the cloud or on your system.