DIAGNOSTIC GUIDE
Mentor Data Quality Audit
Executive Summary
A mentor data quality audit quantifies missing skills, duplicate records, expired availability, and untagged sectors across your roster. Programs with more than 20% incomplete profiles should pause bulk matching and run cleanup sprints. Data quality scores predict match success better than roster size—100 clean profiles beat 300 messy ones.
Key Takeaways & Benchmarks
- Measure completeness per required field
- Deduplicate by email and LinkedIn URL
- Validate sector tags against controlled taxonomy
- Flag mentors with no availability in 120+ days
- Score quality A/B/C for match eligibility tiers
Frequently Asked Questions
How long does a cleanup sprint take?
One to two weeks for 150 mentors with automated nudges and coordinator support.
Should low-quality mentors be removed?
Archive from active matching until updated—preserve history for reactivation.
Does Mentor Intelligence score data quality?
Yes. Roster readiness reports rank profiles and batch nudge incomplete mentors.
Next Step for Your Mentor Program
Explore matching quality, roster coverage, and intake workflows on your cohort.
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