Key Last Planner System Metrics to Assess Project Performance in High-Rise Building and Industrial Construction Projects

AbstractThe Last Planner System (LPS) establishes short cycles of planning and control, comprising LP, the make-ready process, short-term planning commitments, identifying reasons for noncompletion, and implementing corrective actions. Most LPS research has covered longitudinal case studies, but qua...

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Bibliographic Details
Published in:Journal of construction engineering and management 2022-01, Vol.148 (1)
Main Authors: Pérez, Daniel, Lagos, Camilo, Fernando Alarcón, Luis
Format: Article
Language:English
Subjects:
Algorithms
Categories
Clustering
Correlation
High rise buildings
Statistical analysis
Statistical methods
Technical Papers
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Summary:AbstractThe Last Planner System (LPS) establishes short cycles of planning and control, comprising LP, the make-ready process, short-term planning commitments, identifying reasons for noncompletion, and implementing corrective actions. Most LPS research has covered longitudinal case studies, but quantitative transversal research is needed to determine the impact of key LPS processes in performance. The researchers aimed to determine the relationships between LPS components and project performance. Twenty three metrics were established to evaluate six components and 253 possible correlations between them. The authors assessed information from 255 projects and found 131 projects, in five categories, with sufficient information to construct the metrics. Two categories had sufficient sample sizes, which produced a sample of 71 high-rise building (HR) and 28 industrial construction (IC) projects. Each sample was assessed separately to test the correlations, and the project categories were compared to determine statistically significant differences. Then, the projects were classified according to their schedule performance outcome, using a clustering algorithm to find differences between high- and low-performance projects. Statistically significant correlations between the six components were found in both samples, six metrics presented statistically significant differences between high and low performance in HR projects and one in IC projects.
ISSN:0733-9364
1943-7862
DOI:10.1061/(ASCE)CO.1943-7862.0002209