Marzouk, M and Enaba, M (2019) Analyzing project data in BIM with descriptive analytics to improve project performance. Built Environment Project and Asset Management, 9(4), pp. 476-488. ISSN 2044-124X
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | association analysis; big data; building information modelling; data analytics; data clustering; trend analysis |
| Index terms: | construction project, methodology, project performance, clustering, building information modelling, data mining, project communication, case study, project data, big data, inspection, information flow, database |
| Subjects: | quality assurance, information systems, data management, project management theory and practice, professional development, production management, research methods, data science, data collection methods |
| Topics: | Digital Applications, Quality Management, Information Management, Project Management, Research Practice |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here