exit-analysis

Solid

Analyze exit interview data and identify retention insights and patterns

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# Exit Interview Analysis Skill ## Overview The Exit Interview Analysis skill provides capabilities for analyzing exit interview data to identify retention insights, patterns, and actionable improvements. This skill enables systematic exit data collection, theme analysis, and retention strategy recommendations. ## Capabilities ### Interview Design - Create exit interview question templates - Design survey instruments - Configure voluntary vs. involuntary paths - Include skip logic and branching - Support multiple collection methods ### Theme Analysis - Analyze exit data for themes and patterns - Apply NLP to open-ended responses - Cluster related feedback - Identify emerging issues - Track theme prevalence ### Turnover Analysis - Calculate voluntary turnover drivers - Segment analysis by demographics - Identify high-risk populations - Compare regrettable vs. non-regrettable - Track trends over time ### Departmental Reporting - Generate department-level exit reports - Compare managers and teams - Identify outlier departments - Create benchmark comparisons - Support manager feedback ### Issue Identification - Identify management and culture issues - Detect compensation concerns - Surface career development gaps - Flag work-life balance issues - Highlight recognition deficits ### Recommendations - Create retention recommendation reports - Prioritize interventions - Estimate impact of changes - Connect to specific actions - Track recommendation implementation ## Usage ...

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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