Predictive Analytics Center
ML-powered forecasts and early warning systems
Model Portfolio Overview
Flight Risk Prediction Model
Current Alerts
127 employees
High risk in next 6 months
Workforce Demand Forecasting
Next 12 months
+2,341 net headcount
Confidence interval: ±156
Learning Effectiveness Prediction
Insight
Top 3 programs predict 85%
ROI Prediction: $1.8M next quarter
Promotion Readiness Model
Ready for promotion
423 employees
Succession gaps: 17 critical roles
Skills Gap Forecasting
Projected critical gaps
8 skill categories
Early warning: Cloud security gap in 4 months
Flight Risk Intelligence
Attrition Prediction & Prevention
Risk Distribution
127
High Risk Employees
Compared to baseline attrition of 12.4%
Flight Risk Drivers Analysis
What's driving attrition risk across all high-risk employees
Click each bar to see affected employees
High Risk Individuals (Top 20)
| Name | Role | Department | Risk Score | Predicted Exit | Key Drivers | Actions |
|---|---|---|---|---|---|---|
| Alex Thompson | Senior Engineer | Engineering | 94% | 45 days | 🔴Compensation gap (-18%) 🔴Low manager rating ⚠️No promotion in 3 years | |
| Maria Garcia | Product Lead | Product | 89% | 67 days | 🔴External recruiter contact ⚠️Peer departures (3) ⚠️Skills underutilized | |
| James Chen | Data Scientist | Analytics | 87% | 52 days | 🔴Workload burnout signals ⚠️Limited career path ⚠️Below market comp | |
| Sarah Williams | Engineering Manager | Engineering | 85% | 78 days | 🔴Team attrition (4 reports left) ⚠️Org restructure stress 🔴Competing offer likely | |
| David Kumar | Senior Designer | Design | 82% | 91 days | ⚠️Remote work policy change ⚠️Project cancellation ⚠️Skill mismatch |
Trend & Pattern Detection
12-month view of predicted vs actual attrition
📌 Engineering spike in March - post-bonus exodus detected
Workforce Demand Forecasting
Headcount Forecast Model
📌 Projected hiring need: Q1-Q2 2026 (+2,341 net headcount)
Role-Specific Demand
| Role Family | Q4 2024 | Q1 2025 | Q2 2025 | Q3 2025 |
|---|---|---|---|---|
| Engineering | +45 | +67 | +89 | +112 |
| Sales | +23 | +34 | +41 | +38 |
| Data Science | +18 | +25 | +32 | +28 |
| Product | +12 | +15 | +18 | +21 |
| Design | +8 | +11 | +14 | +16 |
Promotion Readiness Insights
Ready-Now Candidates
Sarah Johnson
Senior Developer → Engineering Manager
Readiness: 92% (Ready Now)Strengths:
✓ Performance: Top 10% (3 years)
✓ Leadership: Mentored 5 juniors
✓ Technical: Expert in 4 core skills
Development needs:
⚠️ Budget management (complete Finance course)
Fills critical EM gap in Platform team
Michael Chen
Product Manager → Senior Product Manager
Readiness: 89% (Ready Now)Strengths:
✓ Shipped 8 major features
✓ Cross-functional leadership
✓ Customer insights expert
Development needs:
⚠️ Strategic planning experience
Ready to lead enterprise product line
Emily Rodriguez
Data Analyst → Data Scientist
Readiness: 88% (Ready Now)Strengths:
✓ ML certification completed
✓ Published 3 internal research papers
✓ Python/R expert
Development needs:
⚠️ Production ML deployment
Addresses data science hiring gap
Succession Gap Alert
VP of Engineering
John Smith retiring in 8 months
Internal candidates:
0 ready-now, 2 ready-in-12-months
Recommendation:
Accelerate development program OR external hire
Director of Sales
Lisa Wong considering external offer
Internal candidates:
1 ready-now, 3 ready-in-12-months
Recommendation:
Promote internal candidate immediately
Predictive Insights in Action
Prevented 8 Engineering exits in Q2
Predicted risk
12 engineers flagged
Interventions
Retention bonuses, project reassignments, promotion acceleration
Outcome
8 stayed, 4 left (33% better than expected)
Savings
$1.2M (replacement costs)
Optimized Q3 hiring plan
Demand model predicted
+67 engineers needed
Adjusted for internal mobility
-12 positions
Started hiring
2 months earlier than planned
Result
95% roles filled on time vs industry avg 68%
AI-Powered Recommendations
23 high-risk employees in Engineering - schedule retention conversations this week
Data science hiring demand exceeds supply by 45% - consider training internal candidates
Promotion cycle in 4 weeks - 87 ready-now candidates available for advancement
Q1 attrition predicted at 14.2% (above target) - review compensation competitiveness
Quick Actions
Automate insights delivery and scenario planning