TRAINING COURSE: Decision Making Under Uncertainty and Complexity

Decision Analysis and Risk Management

• Fundamentals of decision analysis: identifying objectives, alternatives, and uncertainties
• Quantitative methods for decision analysis: decision trees, Monte Carlo simulation, and sensitivity analysis
• Risk management strategies: risk identification, assessment, mitigation, and monitoring
• Real options analysis: incorporating flexibility into decision-making under uncertainty
• Application of decision analysis and risk management techniques to real-world scenarios

Scenario Planning and Simulation

• Introduction to scenario planning: anticipating alternative futures and building robust strategies
• Scenario development techniques: trend analysis, expert opinion, and scenario workshops
• Simulation modeling: agent-based modeling, system dynamics, and discrete event simulation
• Monte Carlo simulation for scenario analysis and decision support
• Using simulations to test the resilience of strategies in uncertain and complex environments

Adaptive Decision-Making and Heuristics

• Adaptive decision-making strategies: agility, flexibility, and responsiveness
• Behavioral biases in decision-making under uncertainty and complexity
• Heuristics and cognitive shortcuts: their role in decision-making and potential pitfalls
• Strategies for overcoming cognitive biases and improving decision quality
• Adaptive leadership: leading teams and organizations in uncertain and complex environments

Building Resilience and Innovation

• Building resilience in organizations: agility, robustness, and redundancy
• Innovation strategies for navigating uncertainty and complexity
• Design thinking and agile methodologies for innovation and problem-solving
• Collaborative decision-making: leveraging diverse perspectives and expertise
• Developing a culture of learning and experimentation to thrive in uncertain environments