Cost risk assessment in environmental remediation: Towards a causal-chain approach

Civil engineering projects and environmental pollution cleanup are characterized by frequent changes to project plans, designs and specifications. Such changes to a project during construction present several risks to project participants. Assessment approaches used to address these risks often fail to either investigate the root causes of risks or explicitly consider them during assessment. This dissertation proposes a causal-chain approach to identifying, characterizing and quantifying the risk of cost deviations due to changes. The premise of this thesis is that changes during construction are due to materialization of project uncertainties. The proposed approach is an extension of a causal chain-of-events model used for intervention in social programs. The motivation of this research is the betterment of project risk analysis by making it more proactive through identification and possible prevention of problems at their root causes. Data for this study came from change orders of environmental remediation projects on Superfund and Military sites. Many key elements of the causal-chain approach are researched in this dissertation. The research methodology includes: (1) identification of causes of construction changes, (2) study of risk characteristics of changes, and (3) development of predictive models of construction cost deviations. Results of this research indicate that six broad categories of causes are responsible for the bulk of changes in environmental remediation. The variability of the frequency of these changes is random and follows a Poisson distribution. The variability of cost overrun resulting from a change is also random and follows a Lognormal distribution. These two variables were combined in a probabilistic model for predicting expected value and variance of total cost overrun. Statistical regression models of cost overrun were developed to compare with and supplement the probabilistic model. Results show that causal-chain probabilistic model is useful as a predictive model, but can be improved by including additional variables of change. The contributions of this research are: (1) the adaptation of the causal-chain approach to cost risk assessment; (2) a demonstrated use of change order data in understanding project risks; (3) the characterization of cost risks of environmental remediation; (4) the predictive models of cost overrun for environmental remediation.