Pre-Audit Data Preparation Checklist

List every tool that screens, scores, ranks, or recommends candidates — including ATS built-in features and third-party integrations.

Ensure your ATS collects voluntary demographic self-identification data (race/ethnicity, sex/gender) from all applicants.

Export should include: candidate ID, application date, each pipeline stage reached, final disposition, and any AI-generated scores.

Demographics should be in a separate file linked by candidate ID. This maintains privacy while enabling analysis.

NYC LL144 requires audit data from the past year. Ensure your export covers a full 12-month period.

Aim for >70% disclosure rate. If lower, results may lack statistical power. Consider outreach to improve future disclosure.

Strip names, email addresses, phone numbers, and SSNs. Keep only anonymous IDs, demographics, stages, and scores.

Ensure UTF-8 encoding, consistent date formats, no merged cells, and headers in the first row.

Record screening thresholds, keyword lists, scoring weights, and any other AI configuration that affects candidate outcomes.

Know who needs to act on audit findings: HR ops, hiring managers, ATS vendor contacts, legal team.