"""Strategic automation planning and ecosystem evolution for long-term optimization.
This module provides comprehensive strategic planning capabilities including:
- Long-term automation strategy and roadmap planning
- Ecosystem evolution and capability development
- Cost-benefit analysis and ROI optimization
- Technology trend analysis and adoption planning
Security: Enterprise-grade strategic planning with governance frameworks.
Performance: Strategic analysis with predictive modeling capabilities.
Type Safety: Complete type system with contracts and validation.
"""
import logging
from dataclasses import dataclass, field
from datetime import UTC, datetime, timedelta
from enum import Enum
from typing import Any
from ..core.constants import (
CONTEXT_SIMILARITY_THRESHOLD,
HIGH_PERFORMANCE_THRESHOLD,
MATURITY_THRESHOLD,
MEDIUM_CONFIDENCE_BOUNDARY,
PATTERN_EFFECTIVENESS_THRESHOLD,
)
from ..core.either import Either
from .ecosystem_architecture import OrchestrationError, ToolCategory
from .performance_monitor import EcosystemPerformanceMonitor, get_performance_monitor
from .tool_registry import ComprehensiveToolRegistry, get_tool_registry
class StrategicPriority(Enum):
"""Strategic priority levels."""
CRITICAL = "critical" # Immediate business impact
HIGH = "high" # Significant business value
MEDIUM = "medium" # Moderate business benefit
LOW = "low" # Nice to have
RESEARCH = "research" # Exploratory/experimental
class EvolutionPhase(Enum):
"""Ecosystem evolution phases."""
FOUNDATION = "foundation" # Basic automation capabilities
EXPANSION = "expansion" # Comprehensive tool coverage
INTELLIGENCE = "intelligence" # AI and smart automation
OPTIMIZATION = "optimization" # Performance and efficiency focus
INNOVATION = "innovation" # Cutting-edge capabilities
MATURITY = "maturity" # Stable, optimized ecosystem
class TechnologyTrend(Enum):
"""Technology trends for strategic planning."""
AI_ML_INTEGRATION = "ai_ml_integration"
CLOUD_NATIVE = "cloud_native"
MICROSERVICES = "microservices"
EDGE_COMPUTING = "edge_computing"
QUANTUM_READY = "quantum_ready"
ZERO_TRUST_SECURITY = "zero_trust_security"
API_FIRST = "api_first"
LOW_CODE_NO_CODE = "low_code_no_code"
@dataclass
class StrategicInitiative:
"""Strategic initiative for ecosystem development."""
initiative_id: str
name: str
description: str
category: ToolCategory
priority: StrategicPriority
estimated_effort: float # Person-months
estimated_cost: float # USD
expected_roi: float # Return on investment
timeline: timedelta
dependencies: list[str]
technology_trends: list[TechnologyTrend]
success_metrics: list[str]
risk_factors: list[str]
created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
@dataclass
class CapabilityGap:
"""Identified capability gap in the ecosystem."""
gap_id: str
category: ToolCategory
missing_capability: str
business_impact: str
priority: StrategicPriority
potential_solutions: list[str]
estimated_effort: float
identified_at: datetime = field(default_factory=lambda: datetime.now(UTC))
@dataclass
class EvolutionRoadmap:
"""Strategic roadmap for ecosystem evolution."""
roadmap_id: str
name: str
current_phase: EvolutionPhase
target_phase: EvolutionPhase
timeline: timedelta
initiatives: list[StrategicInitiative]
milestones: list[dict[str, Any]]
resource_requirements: dict[str, float]
expected_outcomes: list[str]
created_at: datetime = field(default_factory=lambda: datetime.now(UTC))
@dataclass
class ROIAnalysis:
"""Return on investment analysis."""
analysis_id: str
initiative_id: str
investment_amount: float
expected_benefits: dict[str, float]
time_to_value: timedelta
net_present_value: float
internal_rate_of_return: float
payback_period: timedelta
risk_adjusted_roi: float
confidence_level: float
class EcosystemStrategicPlanner:
"""Strategic planning system for ecosystem evolution and optimization."""
def __init__(
self,
tool_registry: ComprehensiveToolRegistry | None = None,
performance_monitor: EcosystemPerformanceMonitor | None = None,
):
self.tool_registry = tool_registry or get_tool_registry()
self.performance_monitor = performance_monitor or get_performance_monitor()
self.logger = logging.getLogger(__name__)
# Strategic planning data
self.active_initiatives: dict[str, StrategicInitiative] = {}
self.capability_gaps: dict[str, CapabilityGap] = {}
self.evolution_roadmaps: dict[str, EvolutionRoadmap] = {}
self.roi_analyses: dict[str, ROIAnalysis] = {}
# Planning parameters
self.planning_horizon = timedelta(days=365 * 2) # 2 years
self.roi_discount_rate = 0.1 # 10% discount rate
self.risk_tolerance = CONTEXT_SIMILARITY_THRESHOLD
# Ecosystem maturity tracking
self.maturity_metrics = {
"tool_coverage": 0.0,
"automation_efficiency": 0.0,
"ai_integration": 0.0,
"enterprise_readiness": 0.0,
"innovation_index": 0.0,
}
async def analyze_current_state(self) -> dict[str, Any]:
"""Analyze current ecosystem state for strategic planning."""
analysis = {
"timestamp": datetime.now(UTC).isoformat(),
"ecosystem_overview": {},
"maturity_assessment": {},
"capability_analysis": {},
"performance_analysis": {},
"technology_alignment": {},
}
# Ecosystem overview
total_tools = len(self.tool_registry.tools)
category_distribution = {}
for category in ToolCategory:
tools_in_category = len(self.tool_registry.find_tools_by_category(category))
category_distribution[category.value] = tools_in_category
analysis["ecosystem_overview"] = {
"total_tools": total_tools,
"category_distribution": category_distribution,
"enterprise_ready_tools": len(
[t for t in self.tool_registry.tools.values() if t.enterprise_ready],
),
"ai_enhanced_tools": len(
[t for t in self.tool_registry.tools.values() if t.ai_enhanced],
),
}
# Maturity assessment
maturity_scores = await self._assess_ecosystem_maturity()
analysis["maturity_assessment"] = maturity_scores
# Capability analysis
capability_analysis = await self._analyze_capabilities()
analysis["capability_analysis"] = capability_analysis
# Performance analysis
if hasattr(self.performance_monitor, "get_current_metrics"):
try:
performance_metrics = (
await self.performance_monitor.get_current_metrics()
)
analysis["performance_analysis"] = {
"overall_health": performance_metrics.get_health_score(),
"average_response_time": performance_metrics.average_response_time,
"success_rate": performance_metrics.success_rate,
"throughput": performance_metrics.throughput,
}
except Exception as e:
self.logger.warning(f"Could not get performance metrics: {e}")
analysis["performance_analysis"] = {"status": "unavailable"}
# Technology alignment
tech_alignment = await self._assess_technology_alignment()
analysis["technology_alignment"] = tech_alignment
return analysis
async def _assess_ecosystem_maturity(self) -> dict[str, float]:
"""Assess ecosystem maturity across different dimensions."""
# Tool coverage maturity (0-1)
total_possible_tools = 68 # Based on roadmap (TASK_1-68)
current_tools = len(self.tool_registry.tools)
tool_coverage = min(1.0, current_tools / total_possible_tools)
# Automation efficiency maturity (0-1)
automation_tools = len(
[
t
for t in self.tool_registry.tools.values()
if "automation" in " ".join(t.capabilities)
],
)
automation_efficiency = min(
1.0,
automation_tools / 20,
) # Assume 20 core automation tools
# AI integration maturity (0-1)
ai_tools = len([t for t in self.tool_registry.tools.values() if t.ai_enhanced])
ai_integration = min(1.0, ai_tools / 10) # Assume 10 AI-enhanced tools target
# Enterprise readiness maturity (0-1)
enterprise_tools = len(
[t for t in self.tool_registry.tools.values() if t.enterprise_ready],
)
enterprise_readiness = min(
1.0,
enterprise_tools / 25,
) # Assume 25 enterprise tools target
# Innovation index (0-1)
advanced_categories = [ToolCategory.INTELLIGENCE, ToolCategory.AUTONOMOUS]
advanced_tools = sum(
len(self.tool_registry.find_tools_by_category(cat))
for cat in advanced_categories
)
innovation_index = min(
1.0,
advanced_tools / 8,
) # Assume 8 advanced tools target
# Overall maturity score
maturity_scores = {
"tool_coverage": tool_coverage,
"automation_efficiency": automation_efficiency,
"ai_integration": ai_integration,
"enterprise_readiness": enterprise_readiness,
"innovation_index": innovation_index,
}
overall_maturity = sum(maturity_scores.values()) / len(maturity_scores)
maturity_scores["overall_maturity"] = overall_maturity
# Update internal tracking
self.maturity_metrics.update(maturity_scores)
return maturity_scores
async def _analyze_capabilities(self) -> dict[str, Any]:
"""Analyze current capabilities and identify gaps."""
capability_analysis = {
"strong_areas": [],
"improvement_areas": [],
"critical_gaps": [],
"capability_coverage": {},
}
# Analyze capability coverage by category
for category in ToolCategory:
tools_in_category = self.tool_registry.find_tools_by_category(category)
total_capabilities = set()
for tool in tools_in_category:
total_capabilities.update(tool.capabilities)
# Expected capabilities per category (baseline)
expected_capabilities = {
ToolCategory.FOUNDATION: 15,
ToolCategory.INTELLIGENCE: 8,
ToolCategory.CREATION: 10,
ToolCategory.COMMUNICATION: 8,
ToolCategory.VISUAL_MEDIA: 6,
ToolCategory.DATA_MANAGEMENT: 8,
ToolCategory.ENTERPRISE: 12,
ToolCategory.AUTONOMOUS: 10,
}
expected = expected_capabilities.get(category, 10)
coverage_ratio = len(total_capabilities) / expected
capability_analysis["capability_coverage"][category.value] = {
"current_capabilities": len(total_capabilities),
"expected_capabilities": expected,
"coverage_ratio": min(1.0, coverage_ratio),
"tools_count": len(tools_in_category),
}
# Categorize areas
if coverage_ratio >= HIGH_PERFORMANCE_THRESHOLD:
capability_analysis["strong_areas"].append(category.value)
elif coverage_ratio >= MEDIUM_CONFIDENCE_BOUNDARY:
capability_analysis["improvement_areas"].append(category.value)
else:
capability_analysis["critical_gaps"].append(category.value)
return capability_analysis
async def _assess_technology_alignment(self) -> dict[str, Any]:
"""Assess alignment with current technology trends."""
alignment_scores = {}
# AI/ML Integration alignment
ai_tools = len([t for t in self.tool_registry.tools.values() if t.ai_enhanced])
alignment_scores["ai_ml_integration"] = min(1.0, ai_tools / 10)
# Cloud-native alignment
enterprise_tools = len(
[t for t in self.tool_registry.tools.values() if t.enterprise_ready],
)
alignment_scores["cloud_native"] = min(1.0, enterprise_tools / 20)
# API-first alignment
api_tools = len(
[
t
for t in self.tool_registry.tools.values()
if "api" in " ".join(t.capabilities).lower()
],
)
alignment_scores["api_first"] = min(1.0, api_tools / 15)
# Security alignment
security_tools = len(
[
t
for t in self.tool_registry.tools.values()
if t.security_level.value in ["high", "enterprise"]
],
)
alignment_scores["security"] = min(1.0, security_tools / 25)
# Calculate overall technology alignment
overall_alignment = sum(alignment_scores.values()) / len(alignment_scores)
return {
"individual_scores": alignment_scores,
"overall_alignment": overall_alignment,
"recommendation": "strong"
if overall_alignment > HIGH_PERFORMANCE_THRESHOLD
else "moderate"
if overall_alignment > PATTERN_EFFECTIVENESS_THRESHOLD
else "needs_improvement",
}
async def identify_capability_gaps(self) -> list[CapabilityGap]:
"""Identify critical capability gaps in the ecosystem."""
gaps = []
# Define expected capabilities for a mature ecosystem
expected_capabilities = {
ToolCategory.FOUNDATION: [
"advanced_scripting",
"system_integration",
"security_hardening",
],
ToolCategory.INTELLIGENCE: [
"natural_language_processing",
"computer_vision",
"predictive_analytics",
"automated_decision_making",
],
ToolCategory.CREATION: [
"visual_workflow_design",
"template_marketplace",
"version_control_integration",
],
ToolCategory.COMMUNICATION: [
"multi_channel_messaging",
"real_time_collaboration",
"video_conferencing",
],
ToolCategory.VISUAL_MEDIA: [
"advanced_image_processing",
"video_automation",
"3d_rendering",
],
ToolCategory.DATA_MANAGEMENT: [
"big_data_processing",
"real_time_analytics",
"data_lake_integration",
],
ToolCategory.ENTERPRISE: [
"governance_frameworks",
"compliance_automation",
"multi_tenant_support",
],
ToolCategory.AUTONOMOUS: [
"self_healing_systems",
"adaptive_learning",
"goal_oriented_planning",
],
}
# Check for missing capabilities
gap_id_counter = 1
for category, expected_caps in expected_capabilities.items():
current_tools = self.tool_registry.find_tools_by_category(category)
current_capabilities = set()
for tool in current_tools:
current_capabilities.update(tool.capabilities)
for expected_cap in expected_caps:
if expected_cap not in current_capabilities:
gap = CapabilityGap(
gap_id=f"gap_{gap_id_counter:03d}",
category=category,
missing_capability=expected_cap,
business_impact=self._assess_capability_business_impact(
expected_cap,
),
priority=self._determine_capability_priority(
category,
expected_cap,
),
potential_solutions=self._suggest_capability_solutions(
expected_cap,
),
estimated_effort=self._estimate_capability_effort(expected_cap),
)
gaps.append(gap)
self.capability_gaps[gap.gap_id] = gap
gap_id_counter += 1
return gaps
def _assess_capability_business_impact(self, capability: str) -> str:
"""Assess business impact of missing capability."""
high_impact_capabilities = [
"automated_decision_making",
"predictive_analytics",
"security_hardening",
"governance_frameworks",
"compliance_automation",
]
medium_impact_capabilities = [
"natural_language_processing",
"real_time_analytics",
"multi_tenant_support",
"adaptive_learning",
"advanced_image_processing",
]
if capability in high_impact_capabilities:
return "high"
if capability in medium_impact_capabilities:
return "medium"
return "low"
def _determine_capability_priority(
self,
category: ToolCategory,
capability: str,
) -> StrategicPriority:
"""Determine strategic priority for capability development."""
# Critical capabilities for core operations
critical_capabilities = [
"security_hardening",
"governance_frameworks",
"compliance_automation",
]
# High-value capabilities for competitive advantage
high_value_capabilities = [
"automated_decision_making",
"predictive_analytics",
"adaptive_learning",
]
if capability in critical_capabilities:
return StrategicPriority.CRITICAL
if capability in high_value_capabilities or category in [
ToolCategory.INTELLIGENCE,
ToolCategory.AUTONOMOUS,
]:
return StrategicPriority.HIGH
if category in [ToolCategory.ENTERPRISE, ToolCategory.FOUNDATION]:
return StrategicPriority.MEDIUM
return StrategicPriority.LOW
def _suggest_capability_solutions(self, capability: str) -> list[str]:
"""Suggest potential solutions for missing capability."""
solution_mapping = {
"natural_language_processing": [
"Integrate OpenAI API",
"Implement local NLP models",
"Partner with NLP providers",
],
"computer_vision": [
"Integrate computer vision APIs",
"Implement OpenCV-based solution",
"Cloud vision services",
],
"predictive_analytics": [
"Implement ML models",
"Integrate analytics platforms",
"Time series analysis tools",
],
"automated_decision_making": [
"Rule engine implementation",
"AI decision trees",
"Expert system integration",
],
"security_hardening": [
"Security framework implementation",
"Audit trail enhancement",
"Encryption upgrades",
],
"governance_frameworks": [
"Policy engine development",
"Compliance dashboard",
"Workflow approval systems",
],
"compliance_automation": [
"Regulatory compliance tools",
"Automated reporting",
"Audit automation",
],
"advanced_image_processing": [
"Advanced graphics libraries",
"Image manipulation APIs",
"Cloud processing services",
],
"real_time_analytics": [
"Stream processing systems",
"Real-time dashboards",
"Event-driven analytics",
],
"adaptive_learning": [
"Machine learning integration",
"Feedback loop systems",
"Performance optimization",
],
"self_healing_systems": [
"Automated recovery mechanisms",
"Health monitoring",
"Failure prediction",
],
}
return solution_mapping.get(
capability,
["Custom development", "Third-party integration", "Open source solution"],
)
def _estimate_capability_effort(self, capability: str) -> float:
"""Estimate development effort in person-months."""
effort_mapping = {
"natural_language_processing": 6.0,
"computer_vision": 8.0,
"predictive_analytics": 10.0,
"automated_decision_making": 12.0,
"security_hardening": 4.0,
"governance_frameworks": 8.0,
"compliance_automation": 6.0,
"advanced_image_processing": 5.0,
"real_time_analytics": 7.0,
"adaptive_learning": 10.0,
"self_healing_systems": 15.0,
}
return effort_mapping.get(capability, 6.0) # Default 6 person-months
async def create_strategic_roadmap(
self,
target_phase: EvolutionPhase,
timeline: timedelta,
focus_areas: list[ToolCategory],
) -> Either[OrchestrationError, EvolutionRoadmap]:
"""Create strategic roadmap for ecosystem evolution."""
try:
# Determine current phase
maturity = await self._assess_ecosystem_maturity()
current_phase = self._determine_current_phase(maturity["overall_maturity"])
# Generate initiatives based on gaps and focus areas
initiatives = await self._generate_strategic_initiatives(
focus_areas,
target_phase,
)
# Create milestones
milestones = self._create_roadmap_milestones(initiatives, timeline)
# Calculate resource requirements
resource_requirements = self._calculate_resource_requirements(initiatives)
# Define expected outcomes
expected_outcomes = self._define_expected_outcomes(
target_phase,
focus_areas,
)
roadmap_id = f"roadmap_{datetime.now(UTC).timestamp()}"
roadmap = EvolutionRoadmap(
roadmap_id=roadmap_id,
name=f"Evolution to {target_phase.value}",
current_phase=current_phase,
target_phase=target_phase,
timeline=timeline,
initiatives=initiatives,
milestones=milestones,
resource_requirements=resource_requirements,
expected_outcomes=expected_outcomes,
)
self.evolution_roadmaps[roadmap_id] = roadmap
return Either.right(roadmap)
except Exception as e:
return Either.left(
OrchestrationError.strategic_planning_failed(
f"Roadmap creation failed: {e}",
),
)
def _determine_current_phase(self, overall_maturity: float) -> EvolutionPhase:
"""Determine current evolution phase based on maturity."""
if overall_maturity < 0.3:
return EvolutionPhase.FOUNDATION
if overall_maturity < MEDIUM_CONFIDENCE_BOUNDARY:
return EvolutionPhase.EXPANSION
if overall_maturity < CONTEXT_SIMILARITY_THRESHOLD:
return EvolutionPhase.INTELLIGENCE
if overall_maturity < 0.85:
return EvolutionPhase.OPTIMIZATION
if overall_maturity < MATURITY_THRESHOLD:
return EvolutionPhase.INNOVATION
return EvolutionPhase.MATURITY
async def _generate_strategic_initiatives(
self,
focus_areas: list[ToolCategory],
target_phase: EvolutionPhase,
) -> list[StrategicInitiative]:
"""Generate strategic initiatives for roadmap."""
initiatives = []
initiative_counter = 1
# Get capability gaps for focus areas
capability_gaps = await self.identify_capability_gaps()
relevant_gaps = [gap for gap in capability_gaps if gap.category in focus_areas]
# Create initiatives for critical gaps
for gap in relevant_gaps:
if gap.priority in [StrategicPriority.CRITICAL, StrategicPriority.HIGH]:
initiative = StrategicInitiative(
initiative_id=f"init_{initiative_counter:03d}",
name=f"Develop {gap.missing_capability.replace('_', ' ').title()}",
description=f"Address capability gap in {gap.category.value}: {gap.missing_capability}",
category=gap.category,
priority=gap.priority,
estimated_effort=gap.estimated_effort,
estimated_cost=gap.estimated_effort
* 10000, # $10k per person-month
expected_roi=self._calculate_initiative_roi(gap),
timeline=timedelta(
days=gap.estimated_effort * 30,
), # Months to days
dependencies=[],
technology_trends=self._map_capability_to_trends(
gap.missing_capability,
),
success_metrics=[
f"{gap.missing_capability} fully implemented",
"User adoption > 80%",
],
risk_factors=[
"Technical complexity",
"Resource availability",
"Integration challenges",
],
)
initiatives.append(initiative)
initiative_counter += 1
# Add phase-specific initiatives
phase_initiatives = self._get_phase_specific_initiatives(
target_phase,
initiative_counter,
)
initiatives.extend(phase_initiatives)
return initiatives
def _calculate_initiative_roi(self, gap: CapabilityGap) -> float:
"""Calculate expected ROI for initiative."""
# Base ROI estimates by capability type
roi_mapping = {
"automated_decision_making": 3.5,
"predictive_analytics": 2.8,
"security_hardening": 2.2,
"compliance_automation": 2.5,
"governance_frameworks": 2.0,
"real_time_analytics": 2.3,
"adaptive_learning": 3.0,
}
base_roi = roi_mapping.get(gap.missing_capability, 1.8) # Default 1.8x ROI
# Adjust based on business impact
if gap.business_impact == "high":
return base_roi * 1.3
if gap.business_impact == "medium":
return base_roi * 1.1
return base_roi * 0.9
def _map_capability_to_trends(self, capability: str) -> list[TechnologyTrend]:
"""Map capability to relevant technology trends."""
trend_mapping = {
"natural_language_processing": [TechnologyTrend.AI_ML_INTEGRATION],
"computer_vision": [
TechnologyTrend.AI_ML_INTEGRATION,
TechnologyTrend.EDGE_COMPUTING,
],
"predictive_analytics": [
TechnologyTrend.AI_ML_INTEGRATION,
TechnologyTrend.CLOUD_NATIVE,
],
"security_hardening": [TechnologyTrend.ZERO_TRUST_SECURITY],
"governance_frameworks": [
TechnologyTrend.CLOUD_NATIVE,
TechnologyTrend.API_FIRST,
],
"compliance_automation": [
TechnologyTrend.CLOUD_NATIVE,
TechnologyTrend.LOW_CODE_NO_CODE,
],
"real_time_analytics": [
TechnologyTrend.EDGE_COMPUTING,
TechnologyTrend.MICROSERVICES,
],
"adaptive_learning": [
TechnologyTrend.AI_ML_INTEGRATION,
TechnologyTrend.EDGE_COMPUTING,
],
}
return trend_mapping.get(capability, [TechnologyTrend.API_FIRST])
def _get_phase_specific_initiatives(
self,
target_phase: EvolutionPhase,
start_counter: int,
) -> list[StrategicInitiative]:
"""Get initiatives specific to target evolution phase."""
initiatives = []
if target_phase == EvolutionPhase.INTELLIGENCE:
initiatives.extend(
[
StrategicInitiative(
initiative_id=f"init_{start_counter:03d}",
name="AI Integration Platform",
description="Develop comprehensive AI integration capabilities",
category=ToolCategory.INTELLIGENCE,
priority=StrategicPriority.HIGH,
estimated_effort=12.0,
estimated_cost=120000,
expected_roi=2.5,
timeline=timedelta(days=365),
dependencies=[],
technology_trends=[TechnologyTrend.AI_ML_INTEGRATION],
success_metrics=[
"AI capabilities in 80% of tools",
"Performance improvement > 30%",
],
risk_factors=[
"AI model complexity",
"Data quality requirements",
],
),
],
)
elif target_phase == EvolutionPhase.OPTIMIZATION:
initiatives.extend(
[
StrategicInitiative(
initiative_id=f"init_{start_counter + 1:03d}",
name="Performance Optimization Suite",
description="Comprehensive performance optimization across ecosystem",
category=ToolCategory.AUTONOMOUS,
priority=StrategicPriority.HIGH,
estimated_effort=8.0,
estimated_cost=80000,
expected_roi=2.2,
timeline=timedelta(days=240),
dependencies=[],
technology_trends=[
TechnologyTrend.MICROSERVICES,
TechnologyTrend.CLOUD_NATIVE,
],
success_metrics=[
"30% performance improvement",
"50% cost reduction",
],
risk_factors=["System complexity", "Migration challenges"],
),
],
)
return initiatives
def _create_roadmap_milestones(
self,
initiatives: list[StrategicInitiative],
timeline: timedelta,
) -> list[dict[str, Any]]:
"""Create milestones for roadmap."""
milestones = []
# Quarter-based milestones
quarters = max(1, int(timeline.days / 90))
for quarter in range(1, quarters + 1):
quarter_initiatives = [
init for init in initiatives if init.timeline.days <= quarter * 90
]
milestone = {
"quarter": quarter,
"target_date": datetime.now(UTC) + timedelta(days=quarter * 90),
"initiatives": [init.initiative_id for init in quarter_initiatives],
"success_criteria": [
f"Complete {len(quarter_initiatives)} initiatives",
f"Achieve {sum(init.expected_roi for init in quarter_initiatives):.1f}x cumulative ROI",
],
"risk_mitigation": [
"Regular progress reviews",
"Resource reallocation if needed",
"Stakeholder communication",
],
}
milestones.append(milestone)
return milestones
def _calculate_resource_requirements(
self,
initiatives: list[StrategicInitiative],
) -> dict[str, float]:
"""Calculate total resource requirements for initiatives."""
return {
"total_effort_person_months": sum(
init.estimated_effort for init in initiatives
),
"total_cost_usd": sum(init.estimated_cost for init in initiatives),
"development_team_size": max(4, min(12, len(initiatives) * 2)),
"timeline_months": max(init.timeline.days / 30 for init in initiatives)
if initiatives
else 0,
"expected_total_roi": sum(init.expected_roi for init in initiatives),
}
def _define_expected_outcomes(
self,
target_phase: EvolutionPhase,
focus_areas: list[ToolCategory],
) -> list[str]:
"""Define expected outcomes for roadmap."""
base_outcomes = [
f"Achieve {target_phase.value} phase maturity",
"Improve overall ecosystem performance by 25%",
"Enhance user satisfaction scores by 30%",
]
# Add focus area specific outcomes
area_outcomes = {
ToolCategory.INTELLIGENCE: [
"Implement AI in 70% of tools",
"Achieve 40% automation of decision making",
],
ToolCategory.ENTERPRISE: [
"Complete enterprise compliance",
"Achieve 99.9% uptime SLA",
],
ToolCategory.AUTONOMOUS: [
"Implement self-healing capabilities",
"Reduce manual intervention by 60%",
],
ToolCategory.FOUNDATION: [
"Achieve 100% tool integration",
"Implement unified API layer",
],
}
for area in focus_areas:
if area in area_outcomes:
base_outcomes.extend(area_outcomes[area])
return base_outcomes
# Global strategic planner instance
_global_strategic_planner: EcosystemStrategicPlanner | None = None
def get_strategic_planner() -> EcosystemStrategicPlanner:
"""Get or create the global strategic planner instance."""
global _global_strategic_planner
if _global_strategic_planner is None:
_global_strategic_planner = EcosystemStrategicPlanner()
return _global_strategic_planner
