Primary Author: Alexander M. Ogilvie
Audience Focus: Intermediate
Application Type: Research
Venue: 2016 AACE International Annual Meeting, Toronto, ON, Canada
Abstract: Chaotic systems are defined as nonlinear dynamic systems that are deterministic, highly sensitive to initial conditions, and ultimately unpredictable. This paper explores the concept of projects as chaotic systems by examining the outer tails of a cost growth histogram of more than 1,700 completed manufacturing industry capital projects. The results of the analysis demonstrate that although the logistical complexity of a project plays a role in the predictability of outcomes, much of this seemingly chaotic behavior is explained by failings in human practices and behaviors. A project-based dynamic model necessarily depends on the sensitivity of the project’s initial conditions. In the majority of cases where projects experienced extreme outcomes, either high or low, the outcome’s primary driver was that the project’s initial conditions were not correctly measured. As such, the project management community’s focus should first be on using a means to correctly establish initial conditions for any dynamic model to be rendered representative or useful.
Audience Focus: Intermediate
Application Type: Research
Venue: 2016 AACE International Annual Meeting, Toronto, ON, Canada
Abstract: Chaotic systems are defined as nonlinear dynamic systems that are deterministic, highly sensitive to initial conditions, and ultimately unpredictable. This paper explores the concept of projects as chaotic systems by examining the outer tails of a cost growth histogram of more than 1,700 completed manufacturing industry capital projects. The results of the analysis demonstrate that although the logistical complexity of a project plays a role in the predictability of outcomes, much of this seemingly chaotic behavior is explained by failings in human practices and behaviors. A project-based dynamic model necessarily depends on the sensitivity of the project’s initial conditions. In the majority of cases where projects experienced extreme outcomes, either high or low, the outcome’s primary driver was that the project’s initial conditions were not correctly measured. As such, the project management community’s focus should first be on using a means to correctly establish initial conditions for any dynamic model to be rendered representative or useful.