Stop reacting to resignations—start predicting them. You'll learn how the talent-management cycle (attraction, development, retention) reveals where flight risk hides, and you'll practice flagging high-potential employees at risk of leaving using real workforce data in Excel. Using AI tools like ChatGPT, you'll draft defensible risk explanations that give stakeholders what they need to act. Through realistic role plays where you diagnose a colleague's missed risk signals and defend your own assessment to a skeptical VP, you'll develop the analytical skills that turn HR data into retention decisions. Designed for HR professionals, analysts, and anyone responsible for keeping top talent from walking out the door. Basic spreadsheet familiarity helpful; no HR analytics background required.
Overview
Syllabus
- The Talent-Management Cycle: Where Risk Begins
- Learn how the three stages of the talent-management cycle (attraction, development, retention) create different types of flight risk. You'll diagnose a missed retention signal, understand why high potentials are high risks, and begin analyzing real employee data to spot warning patterns before they become resignations.
- Flagging and Documenting Risk: From Data to Decisions
- Move from analysis to action: flag at-risk employees in your spreadsheet, write defensible explanations for each selection, and use AI to help translate data patterns into stakeholder-ready language. You'll complete a full risk assessment and defend your flags to a skeptical leader who needs to act on your recommendations.
Taught by
Coursera Support and Ritesh Vajariya
