Attributes That Determine the Building Information Modelling Capability Maturity of Quantity Surveying Practice

Abstract

With more than 80% of all construction projects overrunning their budget, there is a need for more efficient management of the estimated 10% of Gross Domestic Product (GDP) that is expended annually on construction across the world. It has been proposed that better information and data management through Building Information Modelling (BIM) will lead to cost savings and greater predictability. Notwithstanding the role of quantity surveyors (QS) in modelling and managing construction cost, they remain among the least capable of assimilating BIM into their existing traditional processes. Despite the increasing need for BIM capability assessments for projects, there remains, no tool specifically developed for assessing QS firm's BIM utilisation capacity or performance. As a result, it is unclear the attributes that indicate BIM capability of QS firms as well as QS practices on projects. This study sought to address this through a review of BIM capability assessment frameworks in order to ascertain their suitability for QS practices. An expert focus group discussion was then used to identify peculiar attributes suitable for QS BIM capability assessment as a precursor to the development of a comprehensive model of QS BIM capability maturity. Findings reveal that most QS BIM capability attributes relate to processes including criteria for effective information definition and data management such that they are consistent with QS measurement standards. The BIM competence of staff also emerged as one of the key attributes highlighting the need for QSs to improve their knowledge, skills and experience in the application of BIM amidst current low levels of adoption. The proposed attributes would assist the development of performance and maturity indicators that would help QS firms better understand their own capability as well as the requirements for delivering costing services through BIM on projects.

An approach for semi-automated data quality assurance within BIM models

“…Similar to focus groups (Creswell, 2013), the workshops allowed the elicitation of industry expert views on the utility and usefulness of the proposed approach while collecting feedback for improvement. Similar approaches have been adopted for testing processes and tools in the BIM domain (Mahamadu et al, 2020). Furthermore, the proposed approach followed up-to-date and current industry progression towards design automation and computational data extraction through rule-based modelling and visual programming (Preidel et al, 2017).…”