Exit Interview Analysis Prompt

Synthesizes exit interview data across multiple departures to identify themes, diagnose push vs. pull factors, surface systemic issues, and generate leadership-ready reports with specific recommendations.

Syntax

hr-and-ai

Exit interview data: [paste anonymized notes from N departures]

Analyze:
1. Top 3-5 themes across exits
2. Clustering by department, manager, tenure, or level
3. Push factors (left because of) vs. pull factors (left for)
4. Accounts suggesting systemic issues not visible in aggregate
5. Summary report for senior leadership with recommendations
6. Three questions to add to future exit interviews

Example

hr-and-ai

// De-identification requirement:
// Remove: names, specific dates, identifiable projects, unique phrases
// Keep: role level, department, tenure range, themes

// Example theme analysis output:
themes: {
  theme1: { label: "Manager quality", frequency: "8/12 exits", cluster: "Two departments", type: "Push" },
  theme2: { label: "Growth opportunity", frequency: "6/12 exits", cluster: "Under 2-year tenure", type: "Pull" },
  theme3: { label: "Compensation", frequency: "5/12 exits", cluster: "Technical roles", type: "Both" }
}

// Recommendation flag:
// 67% of exits cluster in 2 of 8 departments — manager-level intervention needed