Constraction process supervision risk management

Management of risks related to the construction project costs, timing, and quality of work carried out\ud is permanent activity in the construction process. In order to manage this complex activity with\ud significant financial inputs and environmental impacts, appropriate risk management is required. The\ud investor, as key participant in the construction process, has to supervise the construction process in\ud order to adequately manage those financially and technically demanding activities. The role of\ud supervision is very complex, but one can identify its key function - reduction of risks, that could lead\ud to the development of a construction project in an inappropriate way, resulting in project performance\ud failure. In order to ensure more systematic and better decision-making process, and improved risk\ud management in the construction process, a comprehensive risk management framework that could be\ud applied for supervision of building construction was analysed. The main intention of my work was\ud development of conceptual framework enabling quantitative analysis in risk identification and\ud management. During the development of such framework a register of risks which should be managed\ud during the construction supervision was drafted. After that a basic analytical framework, which can be\ud used for quantitative management of uncertainty and risks in construction, was developed. During the\ud development of those analytical tools important missing element for the adequate quantitative risk\ud management was identified: there is no available information or register containing the history of\ud identified unforeseen events and their consequences, which is probably the main obstacle that hinders\ud the shift to quantitative risk management. Despite the lack of data a decision-making model was\ud developed with a scope of validation of the approach. It was developed for a complex set of uncertain\ud events. It is based upon the conditional probabilities using Bayes' Theorem. As a practical example of\ud quantitative conditional probability network, taking into consideration evidence-based statistic, a\ud model was set for uncertainty management in concrete placing