When planning a pipeline replacement program, drinking water companies are faced with a dilemma. On the one hand, factual information about the condition of the water mains will lead to better decisions about which mains to replace, which in turn leads to long-term capital efficiency gains. On the other hand, gathering this information is costly, and only provides financial value when the information leads to a better decision being made. Performing a cost-benefit analysis of the case for data gathering is also difficult, as the benefits are difficult to project. This paper investigates the relationship between the amount of information collected on the condition of water mains and the quality of replacement / rehabilitation decisions made on those mains. A mathematical model based on quantifying the financial risk associated with decision making errors is introduced. This model predicts the financial benefits of information collection programs, as a function of the amount of condition information gathered. An economic optimization equation using the model is presented. This equation yields the Economic Assessment Level: the amount of condition information needed to minimize the total combined spending on information gathering and incorrect decisions. Case studies and examples of the impact of different levels of information gathering are presented. The results of these programs are compared with the predictions of the model, illustrating how the calculations can be used to improve capital improvement program efficiency real world situations.
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