CEO Attrition Risk Radar

CONFIDENTIAL

Attrition Risk Radar CEO Level Report • Q3 Forecast

Business Exposure ₹1.8 Cr

High Risk Headcount 14

Hotspots: Product Eng, Sales North Primary Driver: Manager Quality Action: 72-hr Intervention ROI: 6x

Data as of: Oct 15, 2025 Population: 482 employees Forecast: 90 Days Model Confidence: High

SECTION 1

Where is the attrition risk concentrated right now?

Which 2–3 teams / BUs / locations account for most of the next 60–90 day exit risk?

💡

CEO INSIGHT: 62% of predicted exits are concentrated in 3 teams out of 27.

Risk Heatmap: BU × Location

Top Teams by Risk Score (Pareto)

Team	Headcount	Avg Risk Score	# High Risk	% Contribution

📉 Data Story

While attrition is often viewed as a general issue, today's data proves it is a localized event. Just three teams are driving over 60% of the risk. We do not have a company company-wide problem; we have specific "hotspots" in Product Eng and Sales North.

🚀 CEO ACTION

Immediate Attention: Flag Product Eng, Sales North, and Ops Alpha for HRBP intervention.
Decision: Approve "Risk Halt" meetings for these 3 teams within 72 hours.

🎯 PREDICTED EXITS: The "Hit List" (Next 60 Days)

CONFIDENTIAL • EYES ONLY

Employee	Team	Risk Score	Primary Driver	Performance	Criticality	Recommended Action

SECTION 2

What is the business exposure if we do nothing?

What is the ₹ impact over next 90 days if predicted exits happen?

💡

CEO INSIGHT: Doing nothing may cost ₹1.8 Cr in next quarter from only 14 likely exits.

Expected 90-Day Loss

₹1.8 Cr

▼ High Exposure

Replacement Cost Impact

₹0.9 Cr

50% of Total

Productivity Loss

₹0.6 Cr

Unfilled Roles

Financial Impact Breakdown

Team	Predicted Exits	₹ Exposure

📉 Data Story

Financial exposure analysis reveals that the cost of inaction is asymmetric. Losing Product Eng talent is 3x more expensive than Ops roles due to ramp-up time. The ₹1.8 Cr figure is a conservative estimate including only direct replacement and lost productivity.

🚀 CEO ACTION

Budget Allocation: Allocate ₹30L retention budget to protect ₹1.8Cr exposure (6x ROI).

🧩 Operational Impact (Business Continuity Risk)

Employee	Critical Project	Replacement Time	Delivery Impact

SECTION 3

Are we losing the ‘wrong’ people?

Is predicted attrition concentrated in high performers, critical roles, scarce skills?

💡

CEO INSIGHT: 48% of predicted exits are high performers in hard-to-replace roles.

Risk vs Performance Matrix

Exits by Role Criticality

Role	Risk Level	Scarcity

📉 Data Story

The "Quality Risk" is alarming. We are not shedding low performers; we are at risk of losing our best. The concentration of risk in the "High Performer / Critical Role" quadrant suggests that our most capable people are the ones most likely to leave.

🚀 CEO ACTION

Priority Defense: HRBP to execute "Stay Interviews" with the 6 identified Critical High Performers by Friday.

SECTION 4

What’s driving the risk?

Is this pay issue, manager issue, growth issue, or workload issue?

💡

CEO INSIGHT: Manager quality explains 37% of risk, pay only 12%.

Driver Contribution (Shapley Values)

Variance by Team

Driver	Impact %	Worst Team

📉 Data Story

Root cause analysis confirms that Manager Quality is the primary lever. While pay is a factor, it is secondary. Employees are leaving bad bosses, not bad companies. Focused coaching interventions are expected to yield higher ROI than blanket pay raises.

🚀 CEO ACTION

Intervention: Initiate management coaching for the 3 teams with lowest Manager Quality scores immediately.

👔 Manager Risk Scorecard

Manager	Team Risk	Issue

🗣 HRBP Conversation Guide

For the Manager:

"How often are you doing 1:1s with [Name]?"
"When was the last career discussion?"
"Is workload distributed unevenly?"

For the Employee:

"Do you see a clear growth path here?"
"What is your biggest frustration currently?"
"On a scale of 1-10, how burnt out are you?"

SECTION 5

What intervention reduces risk fastest (ROI view)?

What should we do, where, and what will it save?

💡

CEO INSIGHT: Fixing 4 managers and correcting pay for 6 employees can reduce ₹1.2 Cr exposure at ₹18L cost.

Intervention ROI Roadmap

Team	Action	Cost (Inv.)	Risk Reduction	₹ Saved	ROI

Risk Trajectory: Do Nothing vs. Intervention

📉 Data Story

The ROI model projects that a targeted investment of ₹18 Lakhs can safeguard ₹1.2 Crores of business value. This 6x return metric justifies the immediate budget allocation.

✅ This Week's Intervention Queue

🚀 CEO ACTION

Greenlight: Approve ₹18L Intervention Plan to save ₹1.2Cr.
Timeline: Review progress in 30 days.

SECTION 6

Did our interventions work?

30-day lookback on risk reduction actions.

📈 Risk Reduction Tracker

Team	Risk Before	Action Taken	Risk Now	Improvement

APPENDIX

Analytics Methodology & Technical Basis

How was this data calculated and modeled?

Report Insight	Analytics Technique Used	What This Means
Attrition Risk Score	Weighted Risk Index Model	Multiple signals (tenure, performance, pay gap, manager score, workload) are combined into a single predictive score.
Risk Concentration	Pareto Analysis (80/20 rule)	Identifies small pockets (teams/locations) causing the majority of the risk.
Business Exposure (₹)	Cost of Attrition Financial Model	Combines replacement cost, ramp-up time, and productivity loss to value the risk.
Quality Risk	Cross Segmentation (Risk × Perf × Crit)	Identifies if high performers in critical roles are at risk (Regrettable Attrition).
Driver Contribution	Shapley Value / Feature Importance	Statistically identifies which specific factor (Manager, Pay, etc.) contributes most to the risk score.
Manager Risk Scorecard	Team Risk Aggregation Model	Aggregates individual employee risk scores under each reporting manager.
Intervention ROI	Scenario Simulation	Simulates the reduction in risk probability vs. the cost of specific interventions.
Risk Trajectory	Predictive Trend Modeling	Projects future exposure accumulation if no action is taken.
Impact Tracker	Before/After Measurement	Measures effectiveness of interventions by comparing risk scores over time.