When an employer is preparing for a pay equity analysis, one of the steps is to group comparable jobs.
Pay equity isn’t paying the employees doing the same job the same pay. It is about analyzing the pay of employees doing comparable jobs.
So, “comparable jobs” refer to the positions where the skills and work are similar. You need to identify jobs that have similar responsibilities and value to the employer.
This means that accurate job descriptions are the foundation. The content of jobs within an organization includes:
· Knowledge, skills, and abilities
· Job duties and responsibilities
· Years of relevant experience
· Training, certifications, and education requirements
· Technical and management competencies
· Physical requirements
Often these factors are used to define career levels which are then assigned to jobs based on a review of the job description.
The combination of job families and career levels can become the comparable job groupings that are used in the pay equity analysis.
These components are part of a job architecture framework that ideally has been implemented before the pay equity analysis is conducted.
The data categories used to analyze pay are employee demographics, compensation, and job content.
· Employee demographics includes gender, ethnicity, race, tenure, time in position, etc.
· Compensation includes base salary or hourly pay rates as well as bonuses, commissions, overtime, allowances, and other forms of pay. (Don’t forget to include other rewards like benefits, paid time off, etc. if they are discretionary or negotiable.)
· Employee related data includes performance ratings, years of relevant job experience, education, age (as an indicator of experience), employee education/training, skills, etc.
When I work with employers to do a pay equity audit, often the accuracy of the employee demographics and other data is uncertain and is not available for all employees.
A pay equity analysis is only as good as the data it is based on. So, prioritize the review and validation of employee data to ensure it is accurate and complete.
Make sure the compensation data is accurate, and any discretionary decisions are made based on standard processes.
Incorrect conclusions and flawed decisions from a pay equity analysis are the result of not having good data governance as well as job content and architecture in place.
#compensation #rewards #jobarchitecture #payequity #paytransparency #fairpay #hr #humanresources #pay