Keywords: design, errors, construction, learning, rework, system dynamics.

Design induced rework has been found to contribute to 70% of the total amount of rework that is incurred in projects. Having to unnecessarily repeat activities or processes that were incorrectly implemented can adversely affect the profitability, performance and reputation of those organization(s) involved in the project. This is particularly the case in construction projects where rework, which invariably results from design errors or design changes, has been acknowledged as being the primary factor contributing to time and cost overruns.

Projects may often appear to be going smoothly until nearing completion, when errors made during their formative stages are discovered necessitating costly rework. Of more importance is that design errors, if undetected, may lead to geotechnical or structural failures, which can have catastrophic consequences including severe injuries and even fatalities. 'High profile' construction and engineering failures that have led to fatalities include the Teton Dam, Three Mile Island, Chernobyl, West Gate Bridge, Kansas Hyatt Regency and the Paris Charles de Gaulle International Airport. The occurrence of catastrophic failure typically triggers a forensic investigation of engineering and management practices, not least to determine how and why the event happened and what could have been done to prevent it. The information obtained from a forensic investigation can stimulate post rework learning and guide future policy-making decisions, as well as initiating process improvement activities. This paper presents a forensic management approach to managing design-induced rework, based upon the methodology of system dynamics, and aims to determine how and why rework occurred in a commercial construction project. Key factors that contribute to design errors are identified from a review of the literature and used to produce an influence diagram, which forms the basis for examining rework in a case study project. The findings are used to modify the proposed influence diagram and produce a causal model of design rework. Issues identified from the case study are then modelled and simulated to gain an understanding of the complex interactions and consequences of rework.

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