The Challenge

A multi-state charter network was losing 10% of students annually despite investing heavily in academic support programs. Traditional retention strategies weren't working, and leaders couldn't identify which students needed intervention before they disappeared.

Key Pain Points:

• Existing risk indicators (like low income status) failed to predict withdrawal patterns

• Limited staff capacity meant resources were spread across too many "at-risk" students

• Administrators couldn't determine if interventions were helping retention

• No clear data on when intervention would be most effective for different student profiles

The Manta Solution

The charter network deployed Manta to analyze existing student data across attendance, assessment, and demographic dimensions. The system quickly uncovered counterintuitive patterns and provided actionable timeframes that revolutionized their retention approach.

The Analysis

Manta revealed several surprising insights that challenged conventional educational wisdom:

1. Intervention Window Discovery: Manta identified that 25% of withdrawals occur within just 45 days and 50% within 6.6 months - creating a critical early intervention opportunity
   
   

2. Unexpected Risk Profiles: Contrary to assumptions, students with traditional risk factors (low-income, homeless, ELL) had lower withdrawal rates than students with no identified risk factors - revealing a blind spot in their support system
   
   

3. Enrollment Timing Impact: Late-enrolling students were twice as likely to withdraw regardless of academic performance, highlighting an overlooked operational factor affecting retention
   
   

4. Support Program Effectiveness: Students with multiple support programs (like IEP+ELL services) showed better retention than peers with single supports, suggesting integration of services mattered more than quantity

Key Takeaways

1. Critical Timing Windows: The first 45 days are crucial for student retention, with half of all withdrawals occurring within the first 6.6 months
   
   

2. Attendance as Leading Indicator: Students who eventually withdraw show attendance problems (below 80%) weeks or months before traditional warning signs appear
   
   

3. Operational Factors Matter: Late enrollment emerged as a stronger risk factor than many academic and demographic indicators
   
   

4. Integrated Support Shows Promise: Students receiving coordinated, multiple supports showed better retention than those with isolated interventions

These data-driven insights provide a foundation for developing more effective retention strategies targeting specific time periods, attendance thresholds, and support approaches based on actual withdrawal patterns rather than traditional assumptions.