Risk Identification and Quantification of Contingency Reserve Allocation

Abstract

Infrastructure developments in emerging nations heavily rely on construction projects. It has been noted that most infrastructure projects fall short of their budget and timeline targets, resulting in a low return rate on investment. The amount and significance of each risk may vary depending on the project's nature, scale, and complexity. Many projects fail to accomplish their objectives because they are exposed to several hazards. Most projects compute the contingency reserve using the conventional percentages specified in standards, typically 5–10%. A probabilistic model, in which risks are described as probability distribution functions (PDFs) rather than as static values, is now the preferred method for determining contingency reserves for large projects. This shift has occurred over the past 20 years with the development of desktop computing power. This strategy aims to understand project uncertainty better so that risk management strategies can be created on that foundation.
In order to create a "right-sized" contingency model that integrates an explicit understanding of the risks facing a project with the size of the contingency reserve, this research investigates how probabilistic methodologies might be applied.