Introduction
Evidence-based decision-making for HR
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1. The Importance of Data and Evidence in Making Critical Decisions
Transforming HR with data analytics
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Effective problem-solving techniques
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Using the sample dataset
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Diving into the HR data, head first
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Statistics: Correlation and regression analysis
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2. Working with Data Visualization Tools
Seeing is believing: The importance of data visualization
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Employee charts and dashboards explored
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Use decision trees to predict the future
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3. Inferential Statistics
Predicting the future with data from the past
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The chi-squared test to understand relationships
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Use the t-test to understand differences between two groups
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Use ANOVA to understand the differences in three or more groups
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Summary and Cox regression model to predict new hire turnover
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4. Think Like a CFO
Using ROI to explain and convince
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Everyone is billable
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Making $1 million hiring decisions
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5. Root Cause and Validation
HR data benchmarking
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A/B testing HR data or A/B testing and control groups
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Using AI to accelerate HR data knowledge
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6. Case Study: Predicting Turnover Using the Cox Regression Model
Case study: Predicting turnover with control group testing
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Data-driven insights from Piyush Mathur on talent retention
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7. Case Study: Using Workforce Planning to Meet Production Demands
Case study: Using workforce planning to solve a manufacturing labor shortage
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AI-driven strategies for employee retention from Lydia Wu
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8. Case Study: Using Fishbone Analysis to Streamline the Onboarding Process
Case study: Fishbone analysis and Lean Six Sigma
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Data-driven insights on rapid growth from Christy Spilka
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Conclusion
Data storytelling in HR: Driving change with insights
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Ex_Files_AI_Data_Driven_Decision_Making.zip
(82 KB)