turnover-analytics

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Analyze turnover patterns and develop retention strategies with predictive modeling

AI & Automation 814 stars 53 forks Updated today MIT

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Skill Content

# Turnover Analytics Skill ## Overview The Turnover Analytics skill provides capabilities for analyzing turnover patterns, building predictive models, and developing data-driven retention strategies. This skill enables comprehensive turnover understanding and proactive intervention. ## Capabilities ### Turnover Calculation - Calculate turnover rates by segment - Differentiate voluntary vs. involuntary - Track regrettable vs. non-regrettable - Compute annualized rates - Compare to benchmarks ### Survival Analysis - Perform survival analysis on tenure - Build tenure curves by segment - Identify critical tenure periods - Calculate hazard rates - Compare cohort survival ### Predictive Modeling - Build turnover prediction models - Identify risk factors - Calculate flight risk scores - Validate model accuracy - Update models with new data ### Risk Identification - Identify high-risk employees and teams - Flag at-risk talent segments - Monitor risk score changes - Alert managers proactively - Track intervention effectiveness ### Cost Analysis - Analyze turnover cost impacts - Calculate replacement costs - Estimate productivity loss - Model cost avoidance - Support business case ### Intervention Design - Generate retention intervention recommendations - Prioritize interventions by impact - Design targeted programs - Track retention program effectiveness - Measure ROI of retention ## Usage ### Turnover Analysis ```javascript const turnoverAnalysis = { period: { start:...

Details

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

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