Pay equity audits
CRA has experience in a wide range of industries, and our work has withstood the scrutiny of both local and federal agencies. We have helped employers assess and actively manage/mitigate risk under many different laws, uncover potential inequities, and to develop a strategy to fix inequities.
Our consultants combine deep expertise in each phase of the pay equity audit process with cutting edge analytics and in-depth regulatory knowledge to deliver clear answers and concrete action plans.
- Risk assessment: Identify the best analysis to start with based on your risk exposure and needs.
- Audit planning: Define the scope of your project and request relevant data.
- Research: Interview subject matter experts to understand pay practices, discuss data limitations, and develop a model that’s tailored to the employer.
- Regression analysis: Assess group and/or individual differences, summarize the group differences, and identify areas with potential risk.
- Issue identification and mitigation: Develop a mitigation strategy that is suited to the level of risk, budgetary constraints, the employer’s pay philosophy, and applies requisite business rules.
Proactive pay audits
Since 2017, CRA has performed quarterly audits of base salary and total compensation for the 200,000+ employees of a fortune 100 multinational investment bank and financial services company. We provide an overall global pay gap, as well as the pay gap for each country and line of business. Our work also includes providing the management team with summary level graphics and presentation materials of the regression analyses and the mitigation strategy.
CRA was retained by a publicly-traded Fortune 1000 multinational software corporation with more than 9,000 global employees to perform annual audits of salary, on-target earnings, bonus, and stock grants. Through analysis of the company’s global workforce, CRA provided the client with the difference between actual pay and pay predicted by the model, enabling the client to research individuals paid significantly less than the model predicts. Once the audit was complete and individual equity adjustments were implemented, CRA prepared a pay parity analysis the employer disclosed to increase pay transparency with its employees.
CRA assisted a Fortune 500 pharmaceutical firm that was in the process of converting a subsidiary employing nearly 1000 employees into the parent company compensation structure. The pay equity review identified groups of employees who were slotted inappropriately, as well as individual comparisons among newly defined cohorts that required further research. After collecting supplemental information, CRA ran the analysis to confirm that compensation differences were mitigated.
CRA was retained to perform a university-wide pay equity analysis on all tenure-track faculty across departments and schools within a large and prominent state university. Our models took into account the highly specialized market for academic professors; we analyzed common factors impacting employees’ pay as well as factors unique to faculty within tenure-granting institutions. Our work included identifying areas of risk, rerunning models post-remediation, and presenting our findings to a committee of stakeholders.
Federal contractor audit support
When a Fortune 100 technology manufacturer was involved in a major acquisition, CRA validated data from 14 different data sources to assess risks in existing salary, bonus, stock grants, and on-target earnings. CRA supported over 20 compensation audits producing employee-level compensation data and participating in in-person conciliation meetings with the Agency.
CRA was retained by one of the world’s largest online networking platforms to provide audit support to assess gender and race/ethnic equity in salary, bonus, stock grants, and on-target earnings. CRA’s work included building a sales-specific model that factors in an employee’s sales attainment relative to revenue goals. CRA also provided employee-level compensation data to OFCCP for the client and assistance with supplemental data requests.