Comprehensive Model for Construction Readiness Assessment: Fid-Bau Portal

Comprehensive Model for Construction Readiness Assessment

Ibrahim, Michael W. / Labib, Youssef / Veeramani, Dharmaraj / Hanna, Awad S. / Russell, Jeffrey

The construction industry has experienced rapid growth in the last decade, which was not paralleled by a corresponding growth in productivity. A major reason of this stagnant productivity is that project teams often rush into construction without adequately assessing construction readiness. As a result, numerous projects start construction before they are ready to do so, leading to frequent interruptions, rework, out-of-sequence work, delays, and other complications, resulting in poor productivity and project performance. Despite being an industrywide challenge, construction readiness assessment has received limited attention from researchers as a standalone topic. This paper addresses this research gap by determining what quantitatively differentiates a project as construction-ready (CR) from construction-not-ready (CNR). Thus, this paper presents a comprehensive readiness assessment framework comprising 228 binary factors divided into 15 categories. Using data collected from 80 projects, a mathematical model was developed to weight each factor, facilitating their comparison and the determination of their importance. The factors that had the highest weights in differentiating CR from CNR projects include engineering factors relating to the development process of issued-for-construction (IFC) drawings, project team factors relating to forming a multidisciplinary skilled team, and planning factors relating to accounting for project’s hold points and handoffs. Using the calculated weights, the construction readiness score (CRS) is computed, denoting a project’s construction readiness as a percentage. Furthermore, the paper provides data-driven benchmarks to be compared with a new project’s CRS to classify it as CNR, borderline, or CR. The accuracy and applicability of the readiness assessment model were validated using data from 10 additional projects, all of which were correctly classified using the developed assessment model. The findings presented in this paper can help practitioners objectively assess construction readiness while highlighting the factors that should be addressed prior to mobilization, thus improving overall productivity and project performance.