Top-level Schedule Distribution Models
Risk I Track
In the initial stages of a development project, it is sometimes necessary to build a summary-level schedule for planning and budgeting purposes before the day-by-day details of the project are fully defined or understood. However, when uncertainty assessments are performed on schedule networks containing few activities, the distribution forms chosen for individual activity durations can have a significant impact on the overall results. It is therefore important to choose uncertainty distribution forms that accurately represent the behavior of the sub-network of activities represented by each summary activity.
In this paper, we investigated probability theory to see if there were statistical distributions that were well suited to modeling the completion of typical schedule sub-networks consisting of multiple parallel activities. In order to test the applicability of the distributions investigated, we developed an Excel/@Risk tool to compare how various distributions behave versus simulated data from a simplified schedule network. We evaluated numerous distribution forms including: general Beta, PERT Beta, Log-normal, Weibull, Erlang, and Poisson distributions. We concluded that only the general BETA distribution could accurately model a sub-network consisting of multiple parallel paths. We propose additional research to develop Beta parameters to represent a variety of network topologies (e.g. mostly serial/mostly parallel, generous reserves/no reserves, many discrete risks/few discrete risks, etc.).
Tecolote Research, Inc.
Mr. Frederic has been with Tecolote Research since 1983. He is the Chief Scientist of Tecolote’s Santa Barbara Group, which includes offices in Santa Barbara, Ogden, Albuquerque, and Dayton. In his career at Tecolote, Mr. Frederic has logged a wide variety of experience including cost database software development, CER development, technical baseline development, schedule analysis, simulation software development, and cost estimating. His efforts have addressed many aerospace technologies including radars, optical sensors, missile systems, launch vehicles, launch facilities, space vehicles, and aircraft.