Understand how strategic pay transparency and data analytics are reshaping organizational fairness, from policy implementation to employee expectations.
Brian, could you start by sharing a bit about your role at Merit Analytics Group and your journey into the realm of pay equity and transparency?
At Merit Analytics Group, I lead our pay equity consulting services. Merit Analytics Group’s focus is workforce or people analytics, helping companies to most effectively manage their people by looking to disciplined analysis of their own workforce data. Pay equity—and broader equity issues that we consult on—falls well within this broad purview.
I joined Merit Analytics Group after 23 years at Mercer, where I architected the firm’s pay equity offering and led the workforce analytics consulting team. I am lucky at Merit Analytics Group to be a partner to two brilliant women who also led the analytics businesses at Hewitt (a precursor to Aon) and Willis Towers Watson. Together, the three of us have more than 75 years of experience, across 100s of clients—many in the financial services and technology sectors—helping to build out the underpinnings of what is now a key HR pillar: the People Analytics function.
My path to pay equity started after graduate school when I landed a job to statistically test for potential employment discrimination related to litigation. I believed that the same analyses could be run proactively—to help companies find and address issues before lawsuits were filed, and, more importantly, to do the right thing by their employees and strengthen their brands. Today, I am helping companies stand by their commitments to fair pay and employment practices and helping to ensure employees all have opportunities that match fairly to their experiences, competencies and contributions.
What are the key drivers behind the growing adoption of pay transparency strategies in companies today, aside from regulatory requirements?
Regulatory requirements do matter—new state laws as well as new requirements emerging in the EU require employees to post pay ranges, role-by-role. But I think we have been on a journey where the regulations match the trajectory that companies were taking, to meet the demands of various stakeholders, including executives, investors and employees. Getting the full value of an increasingly diverse workforce requires employers to make the case that they are equitable in pay and in providing opportunities. Executives know it and have increasingly made fairness a core principle. Investors know it and have increasingly demanded to know what steps companies are taking and to see the results in the form of metrics.
All said and done, the various pressures mean many organizations have implemented regular, generally annual pay equity review processes and have increased their transparency about those processes and their results.
How have new regulations impacted the way companies structure and communicate pay, particularly with the inclusion of pay ranges in job postings?
Companies have moved to implement or refresh robust job architectures and to update their market pricing activity, all with an eye not only to set the ranges for posting and sharing but also to put into play greater discipline in compensation setting, which reduces the potential for bias. Indeed, such was the intent of the regulations.
Because employees are also more likely to ask about the appropriateness of their own pay when they have access to the relevant range—why they are where they are in that range—employers are doubling down on their pay equity commitments. Pay equity analysis can ensure that employee pay is fair before the employee asks the question and, furthermore, can pinpoint the relevant factors that drive the specific pay outcome (e.g., experience, location, performance) for a manager’s specific communication.
In your experience, how do company values and culture influence the effectiveness of pay transparency initiatives?
To ensure success, executives need to sponsor pay equity efforts. Managers need to know that the equity exercise is an imperative for the firm, so that they don’t try to rationalize gaps identified and return to the prior norm when allocating other pay adjustments. It is helpful to be transparent with managers about the process, so that they are less likely to object to recommendations.
Further, it helps for executives to put their money behind the process, centralizing funding to remedy pay inequities. If the budget for adjustments needs to be reallocated from elsewhere, the barriers are greater, obviously. But it’s also the case that the clear funding emphasizes the priority.
Structures and processes also matter. I’ve seen it in my work—bias creeps in where there is too little direction. Ensuring that managers have clear examples of what it means to be an “exceptional” rated employees vs. “above average” can ensure employees are placed properly and earn the commensurate awards for that placement. Regular refreshes of unconscious bias training can ensure that managers are countering their own potential for bias as they allocate ratings and make pay decisions. And regular pay equity analysis can ensure that course corrections are made where bias gets through.
Can you elaborate on the role of data analytics in assessing pay structures and identifying pay gaps within organizations?
Pay equity analysis consists of three, high-level steps: (1) data compilation, (2) analysis, and (3) remediation.
In the first step, we pull together indicative, employee-level data from company systems, including pay (base pay and incentives) and protected class (e.g., gender, race) but also experience (e.g., tenure), contribution (e.g., performance rating), work location, and role. These latter factors (and others) need to be properly accounted for before one can calculate an all-else-equal pay gap. With regard to role, it is defined by the pay structure and can include the job family and profile, the pay grade, and the market-based midpoint for the job.
In the second step, statistical models rely on the data to predict pay based on legitimate factors (i.e., not gender or race). The models should be run separately for different parts of the organization that pay according to different rules and they should be validated to ensure factors drive pay in a manner that aligns to intent.
In the third step, the models are used to estimate gaps between groups, after accounting for legitimate factors. The same models can be used to recommend consideration of specific pay adjustments for employees who are out of alignment, in areas of the organization facing gaps. Indeed, different pay adjustment strategies can be tested, as we do it in real time by relying on automated routines to assess not just the cost of each but also its impact.
Pay equity analysis both depends upon the pay structure and can help to improve the structure. If the structure is noisy or if managers do not use the structure reliably, gaps will be larger; improving the structure and ensuring its proper utilization will ensure effective measurement and ensure any resulting actions are best targeted. Further, while the pay equity analysis will generally identify employees who are out of alignment with norms and require pay adjustments, it will sometimes identify employees and/or roles that are not properly positioned in the structure. Data and structures, analysis, and remediation (or action based on the analysis) together serve to improve individual equity as well as the consistent and effective utilization of the structures themselves.
What common challenges do companies face when implementing pay equity analyses, and how can they overcome these obstacles?
I’ll comment on three common challenges:
Inadequate review of equity against performance measures – Because performance evaluations can suffer from bias, some employers choose not to control for performance in their pay equity analyses. However, failure to do so ensures that one can’t address potential inequity in the returns to performance. I suggest accounting for performance ratings in pay equity analysis, but implementing separate checks on the performance management process.
Sequential analyses – Reducing gender inequity can increase racial inequity when white women receive pay increases. Solving one issue at a time can lead to a long cycle of repetitive analyses and budgets that are artificially high. Analyses can be run so that gender, race, and intersectional inequities are examined and addressed at the same time.
Processing adjustments for all the “outliers” – Even in cases in which women or minorities are paid less than men and whites, they are not necessarily overrepresented among the most extremely underpaid employees. Because of that, adjusting pay for outliers in all groups will not generally close gaps. I suggest focusing pay adjustments on underpaid classes—ensuring that all groups can receive pay adjustments but steering the adjustments to address underlying inequities.
How do you see employee expectations around pay transparency evolving, and what impact does this have on companies’ compensation strategies?
Employees have more information about pay than ever before—ranges are readily available online and linked to now required postings, and, of course, employees are legally protected if they share information on their pay with one another. So companies need to be ready to respond to questions about pay from employees and they need to be focused on their broad reputations in a challenging labor market. Pay equity analysis will therefore continue to be a priority and those that do not conduct such analyses regularly will move to do so. Greater simplicity in compensation strategies (e.g., paying to the job vs. the individual) and more stringent management of exceptions to policies will be the new norm. In particular, where there is continued discretion, processes to ensure that that discretion is exercised with care (e.g., calibration in performance reviews, management training and program documentation) will be increasingly crucial.
Could you provide examples of how companies have successfully navigated the complexities of pay equity and transparency to foster a fairer workplace?
A number of companies have moved from regular analysis to disclosing their pay gaps. Some have closed their all-else-equal pay gaps, though they also note their continued focus. Still others have disclosed raw pay gaps—average pay differences between groups (e.g., women and men)—and have accordingly moved to assess a broader set of practices that drive potential inequities in opportunity (e.g., promotion and performance management practices). Whether internal and external pressures, including new transparency norms, have moved companies to regular review, or disclosure, or broadening of their equity focus, many prominent companies in the broadly defined Financial Services and Technology sectors have established real (and increasingly verifiable) standards of fairness, which can be verified in their communications.
What legal risks do companies run if they fail to adopt comprehensive pay transparency and equity practices?
Pay inequity continues to bring legal risks. Notices of settlements of class action pay discrimination lawsuits flag that such risks remain, especially for those who are slow to conduct proactive analysis. In the EU, new regulations will bring substantial financial penalties for companies that have unexplained gaps in excess of five percent by gender. Pressure from activist investors continues and having the least transparent or effective strategy among a company’s peers will potentially hurt the company’s valuation.
Finally, what advice would you give to organizations just beginning their journey toward more transparent and equitable pay practices?
A few things:
Structure the analysis to support – and strengthen – your compensation philosophy. Rely on the go-forward compensation structure, to ensure pay adjustments align to that structure. Be wary about relying on regulatory constructs (e.g., affirmative action plans and/or EEO classifications) to define comparable groups, if they are do not truly match to differentiate between employees paid according to different rules.
Ensure consistency across the enterprise. Implement a review process that is consistent across jurisdictions, to ensure all employees know that the same standard is applied everywhere. Note that a state-of-the-art process will be consistent with legal standards in all jurisdictions, even if the exact local standards require further, targeted investigation.
Consider seriously teaming with an expert: There are a lot of decisions that go into a proper pay equity analysis. Experts understand the tools, but also have experience with the specific context, having consulted to many companies. Do-it-yourself solutions put new burdens on your team and their utilization can create risks (e.g., misdirected pay increases, inequities that are unresolved).
Stay Ahead of the Financial Curve with Our Latest Fintech News Updates!
