Production management is an integral part of the industrial construction process. The process lends itself to measurement by means of statistical tools – to help control the process. Reducing the variation or variability in a process is considered a sign of improved quality of the construction process. To quantify variability and distinguish the “vital few, trivial many” causes, control charts are used, that are constantly updated and communicated for timely feedback on process performance. Site-level experience on hundreds of projects suggests key construction performance measures include the variability and mean (average) percentage level of value-adding, productive work activity. The purpose of this paper is to submit that process metrics provides useful insight for constructing ‘lean,’ i.e., producing value efficiently. Measurement of the construction process involves statistical monitoring and analysis of value- and non-value-added work activities during project execution, using cost-effective random sampling of work activity combined with observation of the workflow. Effective application of the technique of work process measurement and continuous improvement includes elimination of non-value-added activity and waste, and ‘just-intime’ manpower scheduling. Using the correct approach and the proper mindset, work process improvement is saving a major U.S. utility significant contractor labor cost on construction, plant overhaul and modification projects. Construction process sampling is a useful ‘diagnostic’ tool for understanding right action by management, supervision and workers alike – to optimize the work environment and create customer value at all times. Experience demonstrates that the quality of the tactical implementation of sampling is as important as the quality of the strategic planning of its use to transform the construction industry.
Construction process variability, construction process work sampling, construction process benchmarking, construction process improvement, construction productivity.