The secret reason you got that raise
Think back to the last time you received an adjustment to your compensation. Were you told that it was because of your performance? Or that it was because you “exceeded expectations” in 360 peer reviews? Did you assume that HR applied deliberate math, sound methodologies and calibrated results fairly and consistently across the organization to reach those conclusions?
For many organizations, there’s a secret about this process. Your manager — or the HR department, for that matter — probably can’t explain, let alone demonstrate with data and sound analysis, the factors that determined your change in pay. Here’s what’s likely really going on.
Most companies want to reward their better-performing employees with more compensation. Along with years of relevant experience, location and tenure, performance is among the most common criteria companies use to determine who gets paid more.
But most of the time, the scary truth is this: Managers use their discretion and subjectively value performance differently. Why? Because they are human. And most companies lack the fundamental tools to know whether their pay policies are operating as intended.
As a labor and employment law attorney and data scientist, I’ve seen firsthand how companies mostly operate in the dark when it comes to consistently and fairly applying pay policies.
Effective pay policies should be fair, consistent and unbiased, and they should adequately incentivize intended behaviors and outcomes. They need to be defensible in a court of law. They should align with what companies have communicated to their employees, managers and executives. When pay policies are implemented inconsistently or based on biased data, they can inadvertently become one of the biggest drivers of pay disparities.
That means that every time your organization changes compensation, it could be exacerbating the problems. And those problems are more than increased legal risk. They include hits to retention, engagement, productivity, morale and overall brand.
As more companies focus on improving fairness in the workplace to help address systemic inequality, employees deserve more transparency. They should be able to know that if an employer says they pay for performance, they actually are doing so.
Companies also deserve better tools to quickly and dynamically analyze compensation data and know with certainty whether their strategy is working as intendedt.
Many leaders have theories on how their pay policies are working, but few have the tools to know for sure. This is because traditionally, companies look to law firms and consultants to conduct pay equity analyses, and few are able to meaningfully and dynamically examine pay policies because it is slow, static and costly.
So when leaders do get a chance to look under the hood, the data is illuminating.
When a major insurance company recently began its pay equity analysis, leaders wanted to account for only one pay policy: performance rating. But as they looked at their data using the right tools, they realized performance ratings were not explaining variation in compensation much at all.
This finding led the team to think differently about pay policies and apply a much more nuanced approach. Another company that held itself out as a pay-for-performance organization found that it was anything but. Once their team examined pay data using the right tools, they realized their performance ratings system favored men.
Across the company, performance scores had little relationship to determining pay. By seeing the actual impact of their policies on compensation, they were able to address the root causes that were creating unfairness. By using the right technology, companies can finally hold a mirror up to their compensation strategies so both employees and employers can be confident that policies are driving valid differences in pay and incentivizing intended behaviors and outcomes, and are not biased or contributing to inequity in organizations.