A Data-Driven Procedure for Cost and Risk Control in Construction Investments: Quantifying Budget Gaps via Expert Scoring and Probabilistic Simulation—Evidence from a Heritage Hotel Project

This project examines how to improve cost and risk management methodologies through data for construction investment projects that are more difficult in nature and include heritage rehabilitation. The primary aim is to determine the extent to which different risk elements affect project costs, and, together with that, to determine an updated maximum project budget with the confidence level being specified. This method attempts to describe the role of an expert and, independently, the expert describes the role of the simulation method probabilistically. In this method, expert opinion is processed with a Frequency-Impact matrix, weighted scaling, and PERT/Monte Carlo to provide the qualitative aspect of the expert to the level of

the quantitative one, which is required for the prediction. This method assists in the more accurate identification and estimation of the monetary value of the fundamental risk drivers. The aim of this method is to redefine project budget upper limits and also to determine whether the established contingency margins are sufficient to assist in the decision to minimize the risk of the costs overruns and to increase the financial predictability of the project. The structure assists in managing the financial uncertainties of the complex construction projects.

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