Top 4 Compensation Decision Biases and How to Overcome Them With Technology

Compensation Bias

Compensation decisions involve an array of stakeholders and a ton of processes—from performance reviews to pay equity matrix and market value. The compensation management process doesn’t happen in a day.

Matching employee expectations with allocated quota while ensuring proper parity with peers is always a constant concern for HR leaders. What’s worse these problems just scratch the tip of the compensation bias iceberg.

Compensation-related decisions are influenced by an array of elements ranging from socio-cultural cues to economic and legal dimensions. Amid the chaos, HR leaders don’t often find the time to notice the most common types of compensation biases. For the first step to tackling these biases is awareness.

Listed below are four types of compensation biases along with tactics you can use to ensure compensation decisions aren’t being guided by them.  

1. Gender bias

While no organization does this intentionally, even perceived gender pay gaps can cause a lot of damages ranging from disengagement to increased cynicism in the workforce. Although there are so many contributing factors to this bias, the major reason is lack of pay transparency.

Revealing a little or a lot about how much your workers are paid can help reduce the gender bias substantially. However, merely implementing pay transparency is completely useless if you have trouble tackling unconscious biases that fester among raters.

When your compensation decisions are made with a logical automated approach that enforces gender pay guidelines and keeps unconscious biases away can remove gender bias from your compensation management process once and for all.

2. Racial bias

A recent PEW Social Trends report shows that racial wage gaps still persist in the US despite some progress. Without conscious efforts to eliminate racial bias, compensation decisions can end up heightening disparities that already harm the minority community.

Tackling a sensitive issue like this needs a ton of data, both market and industry specific pay scale information and internal pay parity matrix. While making skill set and performance the contributing factors to a compensation decision is critical, it is equally important to ensure that aspects like cultural and socio-economic aspects aren’t a part of the decision.

Today’s HR technological advances like Artificial Intelligence can use the historical performance data and compensation information to make intelligent proposals that predict how an organization should go about structuring their compensation structures in the future, so that it removes any unconscious racial gap in the compensation process.

3. Recency bias

Recency bias is most common in HR environments that depend on outdated tools like paperwork and spreadsheets for performance appraisals. The human nature of being unable to recall every single aspect of an employee’s performance paves the way to this bias.

When a decision maker bases his/her compensation decision on the most recent performance of an employee, ignoring the entire picture, there is a high chance of missing employee progress, improvements, and other major performance indicators.

While moving from an annual review process to a more frequent review method like monthly or quarterly performance can reduce it to an extent, only moving to a completely automated environment will eliminate this bias altogether with aspects like complete employee appraisal trails, goal setting and alignment, feedback management, and more.

4. Halo/Horns bias

It is human tendency to put people on a pedestal and offer a positive, preposterous review when you think highly of a person. And conversely, it is common to offer unfavorable reviews for people when you have a negative perception about them.

Irrespective of the fact whether it is positive or negative, it is just an inherent aspect of human nature to recall a person’s performance in a manner which aligns with our preconceived notions about that specific employee.

The best way to overcome this bias is injecting automation into your compensation management process. In an automated HR environment, it is easy to collect the perspective of multiple stakeholders ranging from managers to clients and peers. This process of collecting different perspectives on an employee’s performance can factor out halo/horn bias of the compensation equation.

Face your compensation biases

As the expectations of your employees and the economy continue to evolve, new compensation challenges are on the rise. It is important to learn about the most common compensation biases in the compensation management process, so that organizations can put the right policies and procedures in place to tackle them.

For additional help, check out our blog which features content for managers, HR experts, and senior leaders on how to streamline their compensation management process and keep them free from common pitfalls.

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