Evaluating the impact of building information modeling on project performance

There is growing interest among practitioners to measure the benefits of Building Information Modeling (BIM) and demonstrate the impact that BIM has on projects. In recent years, several researchers have used illustrative case studies to demonstrate how adopting BIM for specific uses can improve project performance. However, generalizable findings that may be extended across the industry remain somewhat elusive. This paper presents the results of a quantitative study to examine the impact of BIM use adoption and BIM Execution Planning (BEP) on project performance across a range of project delivery methods. The core research questions guiding the study were (1) does increased BIM use adoption improve project performance, as measured by cost, schedule, and quality metrics? and (2) what role does BEP have in the successful implementation of BIM on a project? By leveraging data from over 200 projects, these questions were answered via a multiple regression analysis.

The results showed a significant positive relationship between BIM use adoption and the speed of delivery, perceived facility quality, and group cohesion within the project team, when controlling for project complexity. There was no evidence to suggest that the level of participation in BEP by members of the project team moderated those relationships. Instead, BEP participation was a significant predictor of BIM use adoption. Projects implementing BEP with either a designer-contractor team or the full project team were associated with increased BIM use adoption compared with projects that did not implement BEP. Despite these key findings, this study revealed a need for a new approach for capturing process data across projects to enable more-detailed future analysis. Prior research, including the data set used in this study, was designed to test macrolevel relationships, and omits many of the details about the specific processes or implementation aspects that drive day-to-day actions. Transitioning to collect a more focused data set, aimed at the microlevel of BIM and BEP implementation, and potentially lean construction practices, would enable a better understanding of the value these tools bring to projects.