The primary goals of this Faculty Early Career Development (CAREER) project are to advance our understanding of how risks at different phases of a product's lifecycle impact the product and its supply chain, and to develop decision technologies that could aid decision makers in effectively managing and mitigating these risks. The following specific issues will be addressed: (1) Characterize the underlying risk drivers that affect products and their supply chains at different phases of a product's lifecycle. (2) Analyze and design mechanisms, such as contracts and organizational structures, to sustain the agility and robustness of supply chains when many trading partners interact. (3) Study the role of real-time information acquired through emerging technologies, such as Radio Frequency IDentification (RFID) and Global Positioning Systems (GPS) in securing supply chains and managing risk. (4) Develop methods and analytical tools to study risks during product transitions, i.e., simultaneous phase-in and phase-out of two generations of products. The project will follow an interdisciplinary approach by merging tools, such as dynamic programming, stochastic programming, control theory, game theory, simulation, and decision analysis which come from disciplines such as Operations Research, Management Science, Economics, and Marketing. Results will be developed and disseminated through collaboration with managers at Intel, Cisco, GM, Agile, and affiliates of Stanford University's programs, such as the Alliance of Innovative Manufacturing and the Global Supply Chain Management Forum. The outcomes of this project will aim at enhancing the curriculum in operations management by developing modules covering basic tools and concepts of risk management in product lifecycles and supply chains, as well as case studies based on research and industry experiences. A well-planned and executed risk management strategy could have avoided many recent supply chain disruptions. Hence, advances in risk management promise tremendously improved efficiencies in supply chain management.
