INSC 71030, Managing Risk and Uncertainty

COURSE PURPOSE

Risk management (RM) is the art, science, and practice of making good choices in the face of consequential uncertainty.  RM is essential to success in all areas of management but especially in the contexts of complexity, novelty, and uncertainty that characterize many contemporary operations management and supply chain endeavors.  This course addresses the major concepts, basic techniques, and key challenges of RM.  It aims to (1) familiarize students with the problems and issues confronting risk managers in several contexts and (2) provide students with the vocabulary, concepts, insights, and tools to address these issues.  As a first course in RM, it provides an overview of several areas and knowledge of foundational tools.  As a generic course in RM, it tries to avoid over-emphasis on the way RM is done in any single industry.

The course emphasizes RM terminology, concepts, models, processes, applications, and limitations.  All work done on and decisions made regarding an operation, project, or supply chain should serve to reduce the portion of its value which is at risk.  Throughout, we will stress the difficult tradeoffs faced by risk managers, the managerial insights, and the underlying assumptions.  We critically analyze many of the tools available to aid a risk manager, looking for possible disconnects with “the real world.”  We relate the topics to practical issues in students’ workplaces, and I provide exposure to a variety of sources of RM information for students’ future use and awareness.

COURSE OBJECTIVES

  • Understand the fundamentals of RM for managerial decisions

  • Understand basic RM activities and responsibilities

  • Understand and apply a standard process for identifying and managing risks

  • Understand the role of RM in the firm

  • Understand the role of quantitative modeling for RM decision support

  • Understand several of the challenges to and limitations of RM

  • Apply statistical and simulation techniques and tools to account for uncertainty and risk

  • Apply RM tools and perspectives to analyze case studies

 

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