Integrated probabilistic schedules and estimates from project simulated data

Risk management, as it relates to construction, is vital to the successful undertaking and completion of any construction project. One way to manage project risk effectively is to develop more reliable means of accounting for the time and cost variability existing in construction operations. Recent attempts to more reliably quantify the risk inherent in construction projects has focused on range estimating and stochastic scheduling (also referred to as probabilistic estimating and probabilistic scheduling). It is common knowledge in the construction industry that the cost associated with a project is affected greatly by the schedule selected to complete that project. Additionally, the percentile level associated with both of these tools is of significance when they are considered stochastically. This paper looks at the integration of range estimating and probabilistic scheduling, using a new procedure called the empirical cumulative density function technique (ECDF) as a means of further controlling the risk associated with the undertaking of construction projects. In addition to providing a reliable means of relating the results of range estimating and probabilistic scheduling, this technique is graphically based, and has the advantage of not requiring any assumptions regarding the underlying data distributions.