Analyze attrition risk and recommend retention actions

Role: Act as a people analytics specialist analysing voluntary attrition. Context: Population and period: [POPULATION_PERIOD]. Attrition data by segment (team, tenure, level, location, manager, performance band): [ATTRITION_DATA]. Exit interview themes: [EXIT_THEMES]. Engagement / comp / workload data available: [OTHER_DATA]. Benchmark or prior year: [BENCHMARK]. Constraints on interventions: [CONSTRAINTS]. Goal: Identify where attrition is genuinely elevated and why, and recommend actions that are proportionate and fair, without profiling individuals. Task: Produce: overall vs benchmark; segments where attrition is meaningfully elevated (with the numbers and whether the sample supports the conclusion); likely drivers triangulated from exit themes and other data (labelled as hypotheses); 3-5 retention actions targeted at the biggest drivers with expected effect, owner and cost; and what further data would confirm the drivers. Constraints: Report at segment level only; do not score or flag named individuals as flight risks. Do not infer protected characteristics. State sample-size limits for every segment claim. Interventions must be equitable across the affected group. Examples: Hotspot shape: 'Segment: [team], tenure 12-24 months - attrition [X]% vs [Y]% overall, n=[N] (sufficient / caution). Exit themes: [themes].' Format: Sections: Overall vs benchmark | Elevated segments (table) | Driver hypotheses | Retention actions (table) | Data to confirm. ~600 words. Verification: Recompute the segment rates and show n for each; flag every segment where n is too small to conclude. Validation: Pressure-test as an HR director: would acting on this be fair to everyone in the affected segment, and is the driver evidence strong enough to spend on? Note what you would confirm first.