AI Workforce Optimization System
Orchestrates 11 specialized AI agents in a DAG-based pipeline to analyze 18 months of historical data, forecast 28-day demand using Holt-Winters, detect anomalies via Isolation Forest, assess staff sentiment and burnout, identify patterns, plan emergency surge capacity, match skills to gaps, optimize budgets, and generate prioritized recommendations with full reasoning chains..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Analysis Configuration - Facility selection, department analysis scope, budget constraints, analysis parameters, and AI agents pipeline setup
Multi-Agent Execution - Agent status tracking, execution log with demand forecasting and sentiment analysis, and real-time tool calls code display
Analysis Results - Potential annual savings, efficiency ratio, key findings summary, and prioritized recommended actions with owners and deadlines
All Recommendations - Priority-ranked action items with confidence scores, cost savings projections, and 28-day demand forecast visualization
AI Agents
Specialized autonomous agents working in coordination
Workflow Coordinator
Complex workforce analysis requires coordinating multiple specialized analyses with dependencies—forecasting needs clean data, recommendations need all analysis outputs. Without orchestration, analyses fail or produce inconsistent results.
Core Logic
Uses Claude 3 Opus to manage workflow coordination, dependency tracking, and state machine orchestration. Validates agent dependencies in a DAG structure. Handles error recovery and cross-agent synthesis. Coordinates 7 execution phases: initialization, data preparation, parallel analysis, pattern/emergency analysis, skills matching, budget optimization, and synthesis.
Data Preparation Agent
Raw healthcare workforce data contains missing values, outliers, and schema inconsistencies that corrupt downstream analysis. HSE data formats require specific normalization.
Core Logic
Performs data validation and missing value imputation using statistical methods. Detects and handles outliers. Normalizes schemas to standard format. Integrates HSE data sources. Processes 547 historical records with 18 months of shift data. Validates data quality metrics including completeness percentage and outlier counts.
Regulatory Compliance Agent
Healthcare facilities must maintain NMBI registration compliance, validate scope of practice, and track CPD requirements. Non-compliance risks patient safety and regulatory penalties.
Core Logic
Verifies NMBI registration status for all professionals in scope. Validates scope of practice aligns with assigned departments. Checks CPD (Continuing Professional Development) compliance. Assesses safe staffing ratios per HSE guidelines. Flags regulatory risks. Achieves 98.7% workforce compliance verification across 156 professionals.
Predictive Analytics Agent
Workforce managers cannot anticipate staffing needs without accurate demand forecasts. Traditional scheduling relies on intuition rather than data-driven predictions.
Core Logic
Implements Holt-Winters triple exponential smoothing for demand forecasting. Generates 28-day forecasts with confidence intervals. Performs trend decomposition to separate growth, seasonality, and noise. Models Irish holiday impacts (Christmas, St. Stephen's Day, New Year's, bank holidays). Achieves 95.8% accuracy with 4.2% MAPE.
Pattern Deviation Agent
Staffing anomalies—unusual absences, sudden demand spikes, compliance lapses—often go undetected until they become crises. Manual monitoring cannot process the volume of data required.
Core Logic
Applies Z-score detection (threshold 2.5) and Isolation Forest algorithms to identify anomalies. Classifies severity as critical/high/medium/low. Generates pattern deviation alerts with early warning indicators. Maps historical anomalies to identify recurring issues. Achieves 87.3% precision and 82.1% recall on anomaly detection.
Behavioral Analysis Agent
Staff burnout, dissatisfaction, and turnover risk are leading indicators of staffing crises but are difficult to measure systematically. Retention problems emerge too late for intervention.
Core Logic
Analyzes staff satisfaction scores (0-100) across departments. Detects burnout indicators including workload stress, shift fatigue, and work-life balance issues. Predicts retention risk by department using engagement trend analysis. Forecasts turnover probability. Identifies critical areas requiring immediate intervention (e.g., ICU burnout level: High).
Trend Analysis Agent
Workforce patterns—seasonal fluctuations, day-of-week trends, weather correlations—repeat but are invisible without systematic analysis. Managers react to patterns rather than anticipate them.
Core Logic
Identifies seasonal patterns with confidence scores (e.g., Q4 expiration surge: 89% confidence). Detects day-of-week staffing trends. Models Irish holiday impacts on availability. Analyzes cross-department correlation. Correlates weather patterns with call-outs. Provides evidence-based pattern explanations and mitigation recommendations.
Crisis Planning Agent
Healthcare facilities need surge capacity plans for emergencies but lack systematic planning for crisis scenarios, mutual aid coordination, and resource reallocation protocols.
Core Logic
Plans surge capacity with activation triggers (>15% absence rate, >20% demand increase). Coordinates mutual aid partners across facilities. Develops Christmas coverage plans with specific role assignments. Creates crisis scenarios with response protocols. Defines resource reallocation procedures for emergency situations.
Competency Optimization Agent
Skill gaps between available staff and role requirements lead to suboptimal assignments. Cross-training opportunities are missed, and competency verification is inconsistent.
Core Logic
Performs skills-to-role matching against department requirements. Identifies skill gaps with priority rankings (e.g., Critical Care certification gap: Priority 1). Verifies competencies against NMBI scope. Recommends training programs to close gaps. Identifies cross-training opportunities to increase workforce flexibility.
Financial Planning Agent
Workforce budgets must balance multiple competing objectives—quality, coverage, cost efficiency—while respecting constraints. Manual allocation results in suboptimal spending.
Core Logic
Uses Claude 3 Opus for multi-objective optimization balancing quality, cost, and coverage. Applies greedy optimization with constraint satisfaction. Optimizes agency rates against HSE pay scales. Allocates budget across departments including ICU, ED, Medical-Surgical, Pediatrics, and Oncology.
Action Synthesis Agent
Analysis outputs from multiple agents must be synthesized into prioritized, actionable recommendations with clear reasoning. Without synthesis, managers face information overload.
Core Logic
Ranks recommendations by priority (critical/high/medium/low) with confidence scores. Performs impact assessment. Conducts risk-benefit analysis for each recommendation. Optimizes implementation timelines. Generates full reasoning chains with alternatives considered. Produces actionable recommendations like: 'Accelerate Q4 Credential Renewals'.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization