Build a Defensible Pay Equity Dataset
Prepare a pay-equity dataset with clear inclusion rules, clean compensation fields, and documented exclusions.
The reframe: payroll data is a measurement system, not a neutral fact. Define the population Freeze a review date and decide who belongs in scope. Active regular employees, interns, contractors, leave cases, expatriates, and union roles may need different treatment. Do not let the export decide for you. Normalize compensation Base salary, hourly rate, bonus, stock, allowances, and overtime answer different questions. Convert pay to comparable units before analysis, and preserve the raw fields so every transformation can be checked. Keep the exclusion trail Every removed row should have a reason: missing level, temporary assignment, duplicate employee ID, incomplete pay…
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