The Path To Pay Transparency: The Devil is in the Data

As we continue sharing a series of our posts with thoughts and insights on achieving pay transparency and equity, here’s our tip number two! 

In the pursuit of pay transparency, data is critical. What many companies struggle with is making sure they have accurate and manageable data. Here are five foundational data requirements you need to pay attention to while pursuing the path to pay transparency:

1. Data Infrastructure

A solid job architecture of job families, career tracks, and levels is a requirement to enable pay transparency. This allows you to compare compensable factors in a way that ensures you are looking at like-for-like. Without the infrastructure, it is almost impossible to accurately and effectively evaluate your current organization’s pay and it prevents you from being able to transparently educate your employees about how you manage pay. 

2. Demographic Data

If you are on the path to pay transparency, you must do so with eyes wide open to any potential pay equity issues you may have in your organization. This requires you to have demographic data (such as gender, ethnicity, age, etc) in the same system as your compensation data to do accurate analysis. Given the sensitivity of this information, make sure you have looked carefully at your data security and identified only the key players who are responsible for this type of analysis.

3. Systematic Data Definitions

A critical aspect of analyzing your pay data is understanding the pay decisions that have been made over the tenure of an employee that may explain any differences. This can be nearly impossible if you have not established and maintained a common set of definitions for pay changes, such as promotion, lateral move, and transfers. Without these common definitions, it is difficult to decipher when and why pay changes were made to identify any potential missteps.

4. Differentiating Data

When analyzing pay progression and assessing pay decisions for equity it is important to have the right information to tell the story. This could include capturing performance (basic requirement), education, prior/cumulative experience (less common), and skills (emerging). Especially as the workforce evolves and greater priority is placed on skills over tenure, the ability to capture and analyze this type of information is becoming increasingly critical.

5. Data Integration

The power of data is in your ability to access, organize, and analyze it. This requires you to have all data elements accurately captured and structured in a way that you can bring the information together. If you are one of many companies that operate with pay and other critical data sitting in multiple places, now would be the time to prioritize ways to bring the data together – whether that is in a data warehouse, system integrations, or a consolidation of systems.

A foundational requirement to pursue the path to pay transparency and address any equity gaps is to have the right data elements in the right structure with the right tools and skills to accurately synthesize and analyze the information.  

Want to learn more about how Nua can help? Drop us an email at hello@nuahr.com!