7 Steps Toward Pay Equity – Installment #4: Data Analysis

@ Maryhill Museum of Art

In a time of historic income inequality, how can organizations pay employees more equitably?

One option combines data-driven practices with a dedicated, inclusive effort to study salaries, making adjustments where disparities are found.

Please see Installments 1, 2, and 3 for background on the series, where I cover the nuts and bolts of this work (creating pay scales, conducting wage comparability studies). There are lots of additional resources, too!

New Tools to Interpret Data Gathered

Combining an internal pay scale with external wage comparability data will allow organizations to create a pay analysis worksheet. You can use Excel or another spreadsheet software.

Create a pay analysis worksheet:

  1. Add a column to the right side of the wage comparability study. Write a formula that calculates the average wage across all sources, by position (rows).
  2. Add a second column to the right. Enter your current pay scale here, using annual salaries OR hourly rates. (Pick one; use it consistently.)
  3. Add a third column. Write a formula to calculate the difference in average regional wages and your pay scale for each row (position).

Goals for Data Analysis

  Analyze – Pay Scale

  1. High & low wage points across the organization and departments
  2. The % difference in high and low wages (e.g. the CEO receives 15x the lowest paid employee per hour of work performed)
  3. Range of salaries by department
  4. Average wage by position
  5. Mean (average) salary
  6. Median (middle) salary
  7. Average annual wages for bottom 50%
  8. Average annual wages for top 50%
  9. Breakdown of classification by position

Discover – Pay Analysis Worksheet

  • Outliers in data – highly overpaid or underpaid positions relative to market averages
  • Disparities in pay for positions, departments, or employee classes when compared to external data
  • Errors and/or inconsistency in classification for positions (not employees), based on recommended information from external sources (including the IRS).

 Note: Technically a state is a region, so statewide salary data should be used. However, most states are so diverse that “urban” and “rural” are better terms for comparison when seeking similar geographic areas. You might also use a similar-sized city in a different state (same region) as one data point.

 Pay Equity Analysis – Employee Level

You may want a version of the pay analysis worksheet for all employees (vs. positions only). A deeper dive will reveal:

  • Disparities in pay for employees across positions and departments, when compared to peers
  • Individual wages that are not within salary ranges established in the pay scale (if applicable)
  • Ratio of salaried (exempt) to hourly (non-exempt) employees
  • # of part-time and full-time staff
  • # of administrative staff and program/direct services staff
  • Potential disparities in pay across demographic groups (if this information is included)
    • Pay inequality may affect people of color, women, transgender people, young people, elders, those with disabilities, or who are members of any other protected class.

On this last point, regardless of the intent (discrimination, implicit bias or institutional bias) that led to or contributed to any disparities in pay uncovered – the current pay inequity should be thoughtfully addressed.

Reviewing employees’ pay beyond position and classification is important work, yet it’s best undertaken after an organization has corrected any administrative deficiencies (such as the lack of a pay scale, or the first time setting equitable pay rates against external benchmarks).

Why? 1) Making consistent strides toward better compensation practices for all employees will benefit everyone.  2) It can be overwhelming to take on every lens or aspect of equitable pay at one time. If that work is not managed with transparency and appropriate speed, it can cause morale issues.

Additional Resources


Next week we’ll talk about how to productively discuss all this data and make decisions based on it.

If you would like assistance completing a pay scale or wage comparability study, please contact us.

Thanks for reading! Feedback is welcome.

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