Primary Author: Dr. David T Hulett
Audience Focus: Intermediate
Application Type: Research Venue: 2015 AACE International Annual Meeting, Las Vegas, NV, USA
Abstract: Schedule risk analysis explores how unknowns applied to the project schedules may derive a distribution of possible completion dates. Unknowns include known unknowns (we know the cause but do not know whether the risk will occur and/or, if it occurs, its impact on activity durations), unknown unknowns (those risks that are not known today, whether they could be known or not with further inquiry) and “unknown knowns” (we know but do not want to discuss them in a public forum). This paper describes the types of unknowns the methods used to incorporate the unknowns to drive the Monte Carlo simulation of the schedule. Methods include (1) using the 3-point estimate to represent inherent variability and estimating error and bias, (2) using the risk interview to uncover unknown knowns, and (3) expanding the 3-point range for “far future” (in the context of the project) activities. A simple case study shows, through use of Monte Carlo simulation, examples of the methods and of their impact on final answers.
Audience Focus: Intermediate
Application Type: Research Venue: 2015 AACE International Annual Meeting, Las Vegas, NV, USA
Abstract: Schedule risk analysis explores how unknowns applied to the project schedules may derive a distribution of possible completion dates. Unknowns include known unknowns (we know the cause but do not know whether the risk will occur and/or, if it occurs, its impact on activity durations), unknown unknowns (those risks that are not known today, whether they could be known or not with further inquiry) and “unknown knowns” (we know but do not want to discuss them in a public forum). This paper describes the types of unknowns the methods used to incorporate the unknowns to drive the Monte Carlo simulation of the schedule. Methods include (1) using the 3-point estimate to represent inherent variability and estimating error and bias, (2) using the risk interview to uncover unknown knowns, and (3) expanding the 3-point range for “far future” (in the context of the project) activities. A simple case study shows, through use of Monte Carlo simulation, examples of the methods and of their impact on final answers.