Digital construction strategy for project management optimization in a building renovation site: machine learning and big data analysis

The average incidence of design variation and unexpected events related to the delivery of construction sites is about 13% compared to project planning. The objective of this study is to lower this percentage to about 10–11%, using methodologies aimed at configuring effective digital management strategies. The main purpose is to enhance process efficiency and optimization of construction management strategies, as BIM-based digital management approaches allow to predict unforeseen events, reducing negative variation in time and costs. The proposed application case concerns an applied methodology conducted on a 35,000 m2 historical building renovation project, in a central urban context of Rome, owned by a public institutional real estate company. The implementation of the proposed BIM-based digital information management strategies allowed to enhance efficiency in site management, reducing delay’s incidence on construction site delivery of about 3%. Such improvement is related to the reduction of delays deriving from prediction of unexpected events. The application of the proposed methodology radically improved the traditional site management strategy used by the construction company, generating a significant reduction of wastes in time and resources; in fact, the use of AI and ML systems promptly supported decision-making processes. The result is the configuration of a digital process allowing an optimized time and material management process through real-time monitoring of on-site activities, configuring an effective decision-making support system. Moreover, the information model was also developed according to Asset information Model (AIM) requirements able to provide a reliable database for the operation and maintenance phase.