Analyzing project data in BIM with descriptive analytics to improve project performance

Abstract

Purpose The purpose of this paper is to expand the benefits of building information modeling (BIM) to include data analytics to analyze construction project performance. BIM is a great tool which improves communication and information flow between construction project parties. This research aims to integrate different types of data within the BIM environment, then, to perform descriptive data analytics. Data analytics helps in identifying hidden patterns and detecting relationships between different attributes in the database. Design/methodology/approach This research is considered to be an inductive research that starts with an observation of integrating BIM and descriptive data analytics. Thus, the project’s correspondence, daily progress reports and inspection requests are integrated within the project 5D BIM model. Subsequently, data mining comprising association analysis, clustering and trend analysis is performed. The research hypothesis is that descriptive data analytics and BIM have a great leverage to analyze construction project performance. Finally, a case study for a construction project is carried out to test the research hypothesis. Findings The research finds that integrating BIM and descriptive data analytics helps in improving project communication performance, in terms of integrating project data in a structured format, efficiently retrieving useful information from project raw data and visualizing analytics results within the BIM environment. Originality/value The research develops a dynamic model that helps in detecting hidden patterns and different progress attributes from construction project raw data.

Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry

“…In the design cycle, the designed artifacts are demonstrated, evaluated, and improved iteratively. Thereby, processes of LM, VE, BIM, and BDA, which are given in Figure 3, were also identified by compiling the studies of [12,[16][17][18]33,64,[68][69][70][71][72][73][74][75].…”

“…In the design cycle, the designed artifacts are demonstrated, evaluated, and improved iteratively. Thereby, processes of LM, VE, BIM, and BDA, which are given in Figure 3, were also identified by compiling the studies of [12,[16][17][18]33,64,[68][69][70][71][72][73][74][75]. After generating the tentative framework and its processes, expert interviews were used to evaluate the proposed maturity framework according to its processes, since Peffers et al [23] indicated that the evaluation of proposed artifacts could be performed based on expert evaluations, logical argument, technical experiment, subject-based experiment, action research, prototype, case study, and illustrative scenario.…”

Project cost Management Strategy based on Big Data and BIM

“…According to the needs of users, cloud providers can provide three types of public services, namely infrastructure, software and platform services. These delivery models are configured in different combinations [5]. If the cloud environment provided by the supplier can not correct the failure during the peak period of cloud users, it will cause immeasurable losses to users and reduce the overall confidence of cloud users [6].…”

Systematising multidisciplinary sustainable building design processes utilising BIM

“…Some BIM related frameworks are based on the international assessment rating systems (Wong and Fan, 2013; Ansah et al , 2019; Jalaei et al , 2020), while others have created tools that are integrated into BIM design software to automate performance-based decision-making (Santos et al , 2020; Jaewook et al , 2020; Schlueter and Thesseling, 2009; El-Diraby et al , 2017; Edwards et al , 2019). Recent approaches have also employed big data analytics to improve performance (Marzouk and Enaba, 2019). Nonetheless, organisational aspects of BIM-enabled SBD have not been addressed sufficiently in the literature despite the fact that any resources for technology implementations should be split (Wilkinson, 2005; Shelbourn et al , 2007): 40% people, 40% process and 20% technology.…”

“…al., 2020;Schlueter and Thesseling, 2009;El-Diraby, 2017;Edwards et al, 2019). Recent approaches have also employed big data analytics to improve performance (Marzouk and Enaba, 2019). Nonetheless, organisational aspects of BIM-enabled SBD have not been addressed sufficiently in the literature despite the fact that any resources for technology implementations should be split (Wilkinson, 2005;Shelbourn et al, 2007): 40 per cent people, 40 per cent process, and 20 per cent technology.…”