A modified non-linear Monte Carlo methodology is developed to dramatically increase the accuracy of contingency development in complex project. It is achieved through counting of non-linear risk interactions in complex projects consistently that have been completely missed out by the traditional methods.
A modified non-linear Monte Carlo methodology is developed to dramatically increase the accuracy of contingency development in complex project. It is achieved through counting of non-linear risk interactions in complex projects consistently that have been completely missed out by the traditional methods.
Dr Yuri G. Raydugin is Principal Consultant of Risk Services & Solution Inc., a Canadian consulting company. Yuri worked for Royal Dutch Shell, TransCanada Pipelines, SNC-Lavalin, and Saudi Aramco, managing risks of several megaprojects. He has been involved in risk management of projects with combined budget of about $150B. Yuri has an engineering degree in nuclear physics from Urals Polytechnics Institute, Russia, a PhD in physics and mathematics from Russia's Academy of Sciences, and an MBA in business strategy from Henley Management College in England. He is a member of the Association of Professional Engineers and Geoscientists of Alberta (APEGA) and Saudi Council of Engineers (SCE).
Inhaltsangabe
* 1: High-level overview of project risk management * 2: Conventional PRM Methodologies * 3: Overview of conventional risk quantification methods * 4: Overview of unconventional risk quantification methods * 5: Project Zemblanity business case (I): linear Monte Carlo schedule and cost risk analysis (L-SCRA) * 6: A brief introduction to system dynamics * 7: Project system dynamics: a linear case * 8: Introduction to project complexity * 9: Interactions in a project system * 10: A project structure subsystem (PSS) * 11: A project delivery subsystem (PDS) * 12: Project system maturity evaluation * 13: Non-linear multipliers for risk interactions * 14: Non-linear Monte Carlo modeling requirements * 15: Project Zemblanity business case (II): non-linear Monte Carlo schedule and cost risk analysis (N-SCRA) * 16: Project system dynamics: a non-linear case * 17: Spin-off discussions on project complexity * 18: Conclusion
* 1: High-level overview of project risk management * 2: Conventional PRM Methodologies * 3: Overview of conventional risk quantification methods * 4: Overview of unconventional risk quantification methods * 5: Project Zemblanity business case (I): linear Monte Carlo schedule and cost risk analysis (L-SCRA) * 6: A brief introduction to system dynamics * 7: Project system dynamics: a linear case * 8: Introduction to project complexity * 9: Interactions in a project system * 10: A project structure subsystem (PSS) * 11: A project delivery subsystem (PDS) * 12: Project system maturity evaluation * 13: Non-linear multipliers for risk interactions * 14: Non-linear Monte Carlo modeling requirements * 15: Project Zemblanity business case (II): non-linear Monte Carlo schedule and cost risk analysis (N-SCRA) * 16: Project system dynamics: a non-linear case * 17: Spin-off discussions on project complexity * 18: Conclusion
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