Course Description

The goal of this class is to introduce students to the fundamental methods analyzing and mitigating risks involved in managing services that function at the interface of human, natural and engineered systems.

The risk management problem can be considered to be a search for an optimal solution in a space that satisfies a set of system constraints, while minimizing a set of functions that quantify risk in the system. This is both a science and an art, as often such an optimal solution may be impossible to arrive at without compromises and trade-offs. Therefore the selection of the most feasible solution requires a deep insight into the workings of the system and the intrinsic value that each part of it provides. At the same time, it is critical to quantify uncertainties, when and where possible so that mathematical approaches can be used to model different aspects of a service system, and test its sensitivities to different management policies.

The course will span the following topics:

• Definition of risk as a mathematical quantity
  
• Methods used in identifying and classifying different kinds of system uncertainties and associated risks (epistemic vs. aleatory uncertainties, Bayesian vs. frequentist assessment)
  
• Relevant statistical and probabilistic theories used to quantitatively analyze risk, such as:
  
  • Statistical data analysis,
    
  • Systems and process modeling methods such as Markov Chains,
    
  • Optimization,
    
  • Reliability modeling,
    
  • Complex system dynamics - adaptive uncertainty
    
• Industry standard software tools and techniques in quantitative risk analysis, such as:
  
  • RiskAmp (Monte Carlo Simulation),
    
  • Failure Mode and Effects Analysis,
    
  • Life Cycle Analysis,
    
  • Decision Tree Analysis,
    
  • Simulation Based Risk Analysis
    
• Risk management and mitigation plan formulation accounting for the following:
  
  • Cognitive aspects of human decision making,
    
  • Risk perception and communication,
    
  • Role of risk in dynamic task environments.