Skill: Assess Nonprofit Program Impact

Domain

social_sector

Description

Evaluates nonprofit program effectiveness using outcome metrics, cost-effectiveness analysis, and social return on investment (SROI) calculations.

Tags

nonprofit, impact-measurement, sroi, program-evaluation, social-sector

Use Cases

• •Grant application support
• •Program performance review
• •Donor reporting
• •Strategic planning

Proprietary Business Rules

Rule 1: Outcome Achievement Scoring

Weighted scoring of program outcomes against targets with population-adjusted metrics.

Rule 2: Cost-Effectiveness Benchmarking

Cost per outcome compared to sector benchmarks and similar programs.

Rule 3: SROI Calculation

Social return on investment using standardized value proxies.

Rule 4: Sustainability Assessment

Program sustainability scoring based on funding diversity and scalability.

Input Parameters

• •program_id (string): Program identifier
• •program_type (string): Education, health, workforce, etc.
• •outcomes (dict): Achieved outcome metrics
• •targets (dict): Target outcome metrics
• •total_cost (float): Total program cost
• •beneficiaries (int): Number served
• •funding_sources (dict): Funding by source type
• •program_duration_months (int): Program duration

Output

• •impact_score (float): Overall impact score 0-100
• •cost_effectiveness (dict): Cost per outcome metrics
• •sroi_ratio (float): Social return on investment ratio
• •sustainability_score (int): Sustainability rating
• •recommendations (list): Program improvement recommendations

Implementation

The assessment logic is implemented in impact_assessor.py and references benchmarks from CSV files:

• •program_types.csv - Reference data
• •sustainability_thresholds.csv - Reference data
• •impact_score_weights.csv - Reference data
• •parameters.csv - Reference data.

Usage Example

from impact_assessor import assess_impact

result = assess_impact(
    program_id="PROG-2024-001",
    program_type="workforce_development",
    outcomes={"job_placements": 85, "certifications_earned": 120, "wage_increase_pct": 0.25},
    targets={"job_placements": 100, "certifications_earned": 100, "wage_increase_pct": 0.20},
    total_cost=500000,
    beneficiaries=150,
    funding_sources={"government": 0.4, "foundation": 0.35, "corporate": 0.15, "individual": 0.1},
    program_duration_months=12
)

print(f"Impact Score: {result['impact_score']}")
print(f"SROI: {result['sroi_ratio']}:1")

Test Execution

from impact_assessor import assess_impact

result = assess_impact(
    program_id=input_data.get('program_id'),
    program_type=input_data.get('program_type'),
    outcomes=input_data.get('outcomes', {}),
    targets=input_data.get('targets', {}),
    total_cost=input_data.get('total_cost', 0),
    beneficiaries=input_data.get('beneficiaries', 0),
    funding_sources=input_data.get('funding_sources', {}),
    program_duration_months=input_data.get('program_duration_months', 12)
)