Risk-Based Project Decisions in Situations of High Complexity and Deep Uncertainty

Dr Yuri Raydugin is Principal Consultant of Risk Services & Solution Inc©, a Canadian consulting company. Previously Yuri worked for Saudi Aramco, Royal Dutch Shell, TransCanada Pipelines, and SNC-Lavalin managing risks of a number of projects. He has been involved in risk management of mega and large projects with combined budget exceeding $170B. Depending on project context and challenges, Yuri applies a variety of relevant risk management methods and tools –both traditional and advanced – to properly manage project complexity and deep uncertainty, to facilitate project decision-making and to ensure project success.Yuri has an engineering degree in nuclear physics from Urals Polytechnics Institute, Russia, a PhD degree in physics and mathematics from Russia's Academy of Sciences, and an MBA degree in business strategy from Henley Management College in England. He is a member of the Association of Professional Engineers and Geoscientists of Alberta (APEGA). Yuri is an author of several articles on project risk management as well as on various aspects of physics. He is the author of ‘Modern Risk Quantification in Complex Projects: Non-linear Monte Carlo and System Dynamics Methodologies’, Oxford University Press (2020) and ‘Project Risk Management: Essential Methods for Project Teams and Decision Makers’, John Wiley & Sons (2013) as well as the editor of ‘The Handbook of Research on Leveraging Risk and Uncertainties for Effective Project Management’, IGI Global (2017). Yuri has been an associate editor of International Journal of Risk and Contingency Management (IJRCM) and a distinguished reviewer of publications for International Journal of Project Management (IJPM). Born and raised in Ekaterinburg, Russia, Yuri currently lives and works in Calgary, Alberta, Canada.

• Introduction.- PRM and types of project uncertainties.- Overview of DMDU methodologies.- Project complexity concept.- Decision-making framework.- Selection of project options in situations of deep uncertainty.- Development of project schedule and cost contingencies in complex projects.- Cost escalation and exchange-rate volatility risk assessment methods.- High-level overview of simplistic Monte Carlo and parametric risk assessment methods.- Case study 1: applications of a tradition PRM (scoring method).- Case study 2: applications of “linear Monte Carlo” methodology.- Case study 3: applications of “non-linear Monte Carlo” methodology.- Case study 4: selection of project options (a few “futures”).- Case study 5: selection of project options (multiple “futures”).- Case study 6: applications of cost escalation and exchange-rate volatility modelling methods.- Conclusion.