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| import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import json
class OrganizationalResilienceManagement:
def __init__(self):
self.resilience_framework = {}
self.resilience_assessments = {}
self.resilience_metrics = {}
self.improvement_plans = {}
self.crisis_scenarios = {}
self.resilience_training = {}
def create_resilience_framework(self, framework_id, framework_config):
"""Create organizational resilience framework"""
self.resilience_framework[framework_id] = {
'framework_id': framework_id,
'name': framework_config['name'],
'description': framework_config['description'],
'dimensions': framework_config.get('dimensions', []),
'capabilities': framework_config.get('capabilities', []),
'indicators': framework_config.get('indicators', []),
'assessment_criteria': framework_config.get('assessment_criteria', []),
'improvement_areas': framework_config.get('improvement_areas', []),
'maturity_levels': framework_config.get('maturity_levels', []),
'created_date': datetime.now()
}
def conduct_resilience_assessment(self, assessment_id, assessment_config):
"""Conduct resilience assessment"""
self.resilience_assessments[assessment_id] = {
'assessment_id': assessment_id,
'framework_id': assessment_config['framework_id'],
'assessment_date': datetime.now(),
'assessor': assessment_config['assessor'],
'scope': assessment_config['scope'],
'dimensions_assessed': assessment_config.get('dimensions_assessed', []),
'scores': {},
'strengths': [],
'weaknesses': [],
'opportunities': [],
'threats': [],
'overall_score': 0,
'maturity_level': 'initial',
'recommendations': []
}
# Calculate scores per dimension
for dimension in assessment_config.get('dimensions_assessed', []):
dimension_score = self.calculate_dimension_score(dimension, assessment_config)
self.resilience_assessments[assessment_id]['scores'][dimension] = dimension_score
# Calculate overall score
if self.resilience_assessments[assessment_id]['scores']:
overall_score = sum(self.resilience_assessments[assessment_id]['scores'].values()) / len(self.resilience_assessments[assessment_id]['scores'])
self.resilience_assessments[assessment_id]['overall_score'] = overall_score
# Determine maturity level
maturity_level = self.determine_maturity_level(overall_score)
self.resilience_assessments[assessment_id]['maturity_level'] = maturity_level
# Generate recommendations
recommendations = self.generate_resilience_recommendations(assessment_id)
self.resilience_assessments[assessment_id]['recommendations'] = recommendations
return assessment_id
def calculate_dimension_score(self, dimension, assessment_config):
"""Calculate specific dimension score"""
dimension_scores = {
'operational': {
'continuity_planning': assessment_config.get('continuity_planning_score', 0),
'process_flexibility': assessment_config.get('process_flexibility_score', 0),
'redundancy': assessment_config.get('redundancy_score', 0),
'automation': assessment_config.get('automation_score', 0)
},
'technological': {
'system_architecture': assessment_config.get('system_architecture_score', 0),
'cybersecurity': assessment_config.get('cybersecurity_score', 0),
'data_recovery': assessment_config.get('data_recovery_score', 0),
'monitoring': assessment_config.get('monitoring_score', 0)
},
'human': {
'adaptive_leadership': assessment_config.get('adaptive_leadership_score', 0),
'learning_culture': assessment_config.get('learning_culture_score', 0),
'training_development': assessment_config.get('training_development_score', 0),
'communication': assessment_config.get('communication_score', 0)
},
'strategic': {
'adaptive_vision': assessment_config.get('adaptive_vision_score', 0),
'flexible_strategy': assessment_config.get('flexible_strategy_score', 0),
'continuous_innovation': assessment_config.get('continuous_innovation_score', 0),
'risk_management': assessment_config.get('risk_management_score', 0)
}
}
if dimension in dimension_scores:
scores = dimension_scores[dimension]
return sum(scores.values()) / len(scores) if scores else 0
return 0
def determine_maturity_level(self, overall_score):
"""Determine maturity level based on score"""
if overall_score >= 90:
return 'optimizing'
elif overall_score >= 75:
return 'managed'
elif overall_score >= 60:
return 'defined'
elif overall_score >= 40:
return 'repeatable'
else:
return 'initial'
def generate_resilience_recommendations(self, assessment_id):
"""Generate resilience recommendations"""
if assessment_id not in self.resilience_assessments:
return []
assessment = self.resilience_assessments[assessment_id]
recommendations = []
# Recommendations based on low scores
for dimension, score in assessment['scores'].items():
if score < 60:
recommendations.append({
'dimension': dimension,
'priority': 'high',
'description': f"Improve {dimension} resilience (score: {score:.1f})",
'action': f"Develop {dimension} resilience capabilities"
})
elif score < 75:
recommendations.append({
'dimension': dimension,
'priority': 'medium',
'description': f"Optimize {dimension} resilience (score: {score:.1f})",
'action': f"Enhance {dimension} resilience capabilities"
})
# Recommendations based on maturity level
maturity_level = assessment['maturity_level']
if maturity_level == 'initial':
recommendations.append({
'dimension': 'overall',
'priority': 'critical',
'description': 'Establish organizational resilience foundations',
'action': 'Develop basic resilience framework and capabilities'
})
elif maturity_level == 'repeatable':
recommendations.append({
'dimension': 'overall',
'priority': 'high',
'description': 'Standardize resilience processes',
'action': 'Standardize resilience processes and procedures'
})
elif maturity_level == 'defined':
recommendations.append({
'dimension': 'overall',
'priority': 'medium',
'description': 'Manage and measure resilience',
'action': 'Implement resilience management and measurement'
})
elif maturity_level == 'managed':
recommendations.append({
'dimension': 'overall',
'priority': 'low',
'description': 'Optimize organizational resilience',
'action': 'Optimize organizational resilience capabilities'
})
return recommendations
def create_improvement_plan(self, plan_id, plan_config):
"""Create resilience improvement plan"""
self.improvement_plans[plan_id] = {
'plan_id': plan_id,
'name': plan_config['name'],
'description': plan_config['description'],
'assessment_id': plan_config['assessment_id'],
'improvement_areas': plan_config.get('improvement_areas', []),
'objectives': plan_config.get('objectives', []),
'actions': plan_config.get('actions', []),
'timeline': plan_config.get('timeline', {}),
'resources': plan_config.get('resources', []),
'success_metrics': plan_config.get('success_metrics', []),
'status': 'draft',
'created_date': datetime.now(),
'last_updated': datetime.now()
}
def track_improvement_progress(self, plan_id, progress_data):
"""Track improvement progress"""
if plan_id not in self.improvement_plans:
return False
plan = self.improvement_plans[plan_id]
progress_entry = {
'progress_id': f"PROG-{len(plan.get('progress_entries', [])) + 1}",
'date': datetime.now(),
'completed_actions': progress_data.get('completed_actions', []),
'in_progress_actions': progress_data.get('in_progress_actions', []),
'blocked_actions': progress_data.get('blocked_actions', []),
'metrics_achieved': progress_data.get('metrics_achieved', {}),
'challenges': progress_data.get('challenges', []),
'next_steps': progress_data.get('next_steps', []),
'overall_progress': progress_data.get('overall_progress', 0)
}
if 'progress_entries' not in plan:
plan['progress_entries'] = []
plan['progress_entries'].append(progress_entry)
# Update plan status
if progress_entry['overall_progress'] >= 100:
plan['status'] = 'completed'
elif progress_entry['overall_progress'] > 0:
plan['status'] = 'in_progress'
plan['last_updated'] = datetime.now()
return True
def create_crisis_scenario(self, scenario_id, scenario_config):
"""Create crisis scenario for testing"""
self.crisis_scenarios[scenario_id] = {
'scenario_id': scenario_id,
'name': scenario_config['name'],
'description': scenario_config['description'],
'crisis_type': scenario_config['crisis_type'],
'severity_level': scenario_config['severity_level'],
'affected_systems': scenario_config.get('affected_systems', []),
'affected_processes': scenario_config.get('affected_processes', []),
'timeline': scenario_config.get('timeline', {}),
'challenges': scenario_config.get('challenges', []),
'success_criteria': scenario_config.get('success_criteria', []),
'learning_objectives': scenario_config.get('learning_objectives', []),
'created_date': datetime.now()
}
def conduct_resilience_training(self, training_id, training_config):
"""Conduct resilience training"""
self.resilience_training[training_id] = {
'training_id': training_id,
'name': training_config['name'],
'description': training_config['description'],
'training_type': training_config['training_type'],
'participants': training_config.get('participants', []),
'scenario_id': training_config.get('scenario_id'),
'duration_hours': training_config.get('duration_hours', 4),
'scheduled_date': training_config.get('scheduled_date'),
'status': 'scheduled',
'results': {},
'created_date': datetime.now()
}
def execute_resilience_training(self, training_id, execution_data):
"""Execute resilience training"""
if training_id not in self.resilience_training:
return False
training = self.resilience_training[training_id]
training['status'] = 'in_progress'
training['start_time'] = datetime.now()
# Simulate training execution
training_results = {
'training_id': training_id,
'start_time': training['start_time'],
'end_time': training['start_time'] + timedelta(hours=training['duration_hours']),
'participants_attended': len(execution_data.get('participants_attended', [])),
'scenarios_completed': len(execution_data.get('scenarios_completed', [])),
'learning_objectives_met': len(execution_data.get('learning_objectives_met', [])),
'participant_feedback': execution_data.get('participant_feedback', {}),
'instructor_feedback': execution_data.get('instructor_feedback', {}),
'improvement_areas': execution_data.get('improvement_areas', []),
'overall_success': execution_data.get('overall_success', False),
'effectiveness_score': execution_data.get('effectiveness_score', 0)
}
training['results'] = training_results
training['status'] = 'completed'
training['end_time'] = training_results['end_time']
return True
def calculate_resilience_metrics(self, framework_id):
"""Calculate resilience metrics"""
if framework_id not in self.resilience_framework:
return None
# Get framework assessments
framework_assessments = [a for a in self.resilience_assessments.values() if a['framework_id'] == framework_id]
if not framework_assessments:
return None
# Calculate metrics
total_assessments = len(framework_assessments)
avg_overall_score = sum(a['overall_score'] for a in framework_assessments) / total_assessments
# Maturity level distribution
maturity_distribution = {}
for assessment in framework_assessments:
maturity = assessment['maturity_level']
if maturity not in maturity_distribution:
maturity_distribution[maturity] = 0
maturity_distribution[maturity] += 1
# Improvement trends
recent_assessments = [a for a in framework_assessments if a['assessment_date'] >= datetime.now() - timedelta(days=90)]
if len(recent_assessments) >= 2:
recent_scores = [a['overall_score'] for a in recent_assessments]
trend = 'improving' if recent_scores[-1] > recent_scores[0] else 'declining'
else:
trend = 'stable'
# Get active improvement plans
active_plans = [p for p in self.improvement_plans.values() if p['status'] == 'in_progress']
# Get recent training
recent_training = [t for t in self.resilience_training.values() if t.get('scheduled_date', datetime.min) >= datetime.now() - timedelta(days=30)]
metrics = {
'framework_id': framework_id,
'total_assessments': total_assessments,
'avg_overall_score': avg_overall_score,
'maturity_distribution': maturity_distribution,
'trend': trend,
'active_improvement_plans': len(active_plans),
'recent_training_sessions': len(recent_training),
'resilience_level': self.determine_resilience_level(avg_overall_score)
}
return metrics
def determine_resilience_level(self, avg_score):
"""Determine resilience level based on average score"""
if avg_score >= 85:
return 'highly_resilient'
elif avg_score >= 70:
return 'resilient'
elif avg_score >= 55:
return 'moderately_resilient'
elif avg_score >= 40:
return 'developing_resilience'
else:
return 'low_resilience'
def generate_resilience_report(self, framework_id):
"""Generate resilience report"""
if framework_id not in self.resilience_framework:
return None
framework = self.resilience_framework[framework_id]
metrics = self.calculate_resilience_metrics(framework_id)
if not metrics:
return None
# Get recent assessments
recent_assessments = [a for a in self.resilience_assessments.values() if a['framework_id'] == framework_id and a['assessment_date'] >= datetime.now() - timedelta(days=90)]
# Get improvement plans
improvement_plans = [p for p in self.improvement_plans.values() if p['assessment_id'] in [a['assessment_id'] for a in recent_assessments]]
# Generate strategic recommendations
strategic_recommendations = self.generate_strategic_recommendations(metrics, recent_assessments, improvement_plans)
report = {
'framework_id': framework_id,
'framework_name': framework['name'],
'report_date': datetime.now(),
'metrics': metrics,
'recent_assessments': len(recent_assessments),
'improvement_plans': len(improvement_plans),
'strategic_recommendations': strategic_recommendations,
'next_steps': self.generate_resilience_next_steps(metrics, strategic_recommendations)
}
return report
def generate_strategic_recommendations(self, metrics, assessments, improvement_plans):
"""Generate strategic recommendations"""
recommendations = []
# Recommendations based on resilience level
resilience_level = metrics['resilience_level']
if resilience_level == 'low_resilience':
recommendations.append({
'type': 'foundational_development',
'priority': 'critical',
'description': 'Develop organizational resilience foundations',
'action': 'Implement comprehensive resilience framework'
})
elif resilience_level == 'developing_resilience':
recommendations.append({
'type': 'capability_building',
'priority': 'high',
'description': 'Build resilience capabilities',
'action': 'Focus on building specific resilience capabilities'
})
elif resilience_level == 'moderately_resilient':
recommendations.append({
'type': 'optimization',
'priority': 'medium',
'description': 'Optimize existing resilience capabilities',
'action': 'Optimize and enhance current resilience capabilities'
})
elif resilience_level == 'resilient':
recommendations.append({
'type': 'continuous_improvement',
'priority': 'low',
'description': 'Maintain and improve resilience',
'action': 'Maintain and continuously improve resilience'
})
# Recommendations based on trends
if metrics['trend'] == 'declining':
recommendations.append({
'type': 'trend_reversal',
'priority': 'high',
'description': 'Reverse declining resilience trend',
'action': 'Investigate and address factors causing decline'
})
# Recommendations based on improvement plans
if metrics['active_improvement_plans'] == 0:
recommendations.append({
'type': 'improvement_planning',
'priority': 'medium',
'description': 'Develop resilience improvement plans',
'action': 'Create and implement improvement plans'
})
return recommendations
def generate_resilience_next_steps(self, metrics, recommendations):
"""Generate next steps for resilience"""
next_steps = []
critical_recommendations = [r for r in recommendations if r['priority'] == 'critical']
high_recommendations = [r for r in recommendations if r['priority'] == 'high']
if critical_recommendations:
next_steps.append({
'timeline': 'Immediate',
'actions': [r['action'] for r in critical_recommendations],
'priority': 'Critical'
})
if high_recommendations:
next_steps.append({
'timeline': 'Within 1 month',
'actions': [r['action'] for r in high_recommendations],
'priority': 'High'
})
medium_recommendations = [r for r in recommendations if r['priority'] == 'medium']
if medium_recommendations:
next_steps.append({
'timeline': 'Within 3 months',
'actions': [r['action'] for r in medium_recommendations],
'priority': 'Medium'
})
return next_steps
# Usage example
resilience_mgmt = OrganizationalResilienceManagement()
# Create resilience framework
resilience_mgmt.create_resilience_framework('FRAMEWORK-001', {
'name': 'Organizational Resilience Framework 2025',
'description': 'Organizational resilience framework for 2025',
'dimensions': ['operational', 'technological', 'human', 'strategic'],
'capabilities': [
'Continuity Planning',
'Crisis Management',
'Adaptive Leadership',
'Innovation Culture'
],
'maturity_levels': ['initial', 'repeatable', 'defined', 'managed', 'optimizing']
})
# Conduct resilience assessment
assessment_id = resilience_mgmt.conduct_resilience_assessment('ASSESS-001', {
'framework_id': 'FRAMEWORK-001',
'assessor': 'Resilience Team',
'scope': 'organization_wide',
'dimensions_assessed': ['operational', 'technological', 'human', 'strategic'],
'continuity_planning_score': 75,
'process_flexibility_score': 60,
'redundancy_score': 80,
'automation_score': 70,
'system_architecture_score': 85,
'cybersecurity_score': 90,
'data_recovery_score': 75,
'monitoring_score': 80,
'adaptive_leadership_score': 65,
'learning_culture_score': 70,
'training_development_score': 60,
'communication_score': 75,
'adaptive_vision_score': 80,
'flexible_strategy_score': 70,
'continuous_innovation_score': 65,
'risk_management_score': 85
})
# Create improvement plan
resilience_mgmt.create_improvement_plan('PLAN-001', {
'name': 'Resilience Improvement Plan 2025',
'description': 'Resilience improvement plan for 2025',
'assessment_id': assessment_id,
'improvement_areas': ['human', 'strategic'],
'objectives': [
'Improve adaptive leadership capabilities',
'Enhance learning culture',
'Strengthen strategic flexibility'
],
'timeline': {
'start_date': datetime.now(),
'end_date': datetime.now() + timedelta(days=180)
}
})
# Create crisis scenario
resilience_mgmt.create_crisis_scenario('SCENARIO-001', {
'name': 'Cyber Attack Simulation',
'description': 'Massive cyber attack simulation',
'crisis_type': 'cyber_attack',
'severity_level': 'high',
'affected_systems': ['Order Processing', 'Customer Database'],
'challenges': ['Data breach', 'System downtime', 'Customer impact'],
'learning_objectives': [
'Test incident response procedures',
'Evaluate communication effectiveness',
'Assess recovery capabilities'
]
})
# Generate report
report = resilience_mgmt.generate_resilience_report('FRAMEWORK-001')
print(f"Resilience report: {report['framework_name']}")
print(f"Resilience level: {report['metrics']['resilience_level']}")
print(f"Average score: {report['metrics']['avg_overall_score']:.1f}")
print(f"Strategic recommendations: {len(report['strategic_recommendations'])}")
|