Primary Author: Mr. Graham Gilmer and Mr. Eric Druker
Audience Focus: Intermediate
Application Type: Application
Venue: 2014 AACE International Annual Meeting, New Orleans, LA, USA
Abstract: One of the greatest challenges in managing costs on programs is the lack of cost, schedule, and risk integration. Despite the interconnection of these disciplines, it is rare when cost estimates/budgets, schedules, and risk registers are fully integrated into a single model. This lack of integration makes it impossible for leaders to make quick decisions to ensure programs are scoped properly to finish on-time and on-budget. Analytical Program Management (APM) is a methodology, pioneered on highly complex NASA programs, for completely integrating cost, schedule and risk. APM allows projects to immediately determine the cost impacts of schedule growth and vice versa. This paper will present a case study of a large-scale NASA program, reviewing the process of establishing connected artifacts to yield powerful analytic insights for the project team. Through Monte Carlo simulation, the risk-adjusted cost estimate and schedule are generated to enable planning using statistical confidence levels. The APM methodology determines lead drivers of cost and schedule risk, as well as mechanisms for re-planning the program to ensure a more optimal outcome.
Audience Focus: Intermediate
Application Type: Application
Venue: 2014 AACE International Annual Meeting, New Orleans, LA, USA
Abstract: One of the greatest challenges in managing costs on programs is the lack of cost, schedule, and risk integration. Despite the interconnection of these disciplines, it is rare when cost estimates/budgets, schedules, and risk registers are fully integrated into a single model. This lack of integration makes it impossible for leaders to make quick decisions to ensure programs are scoped properly to finish on-time and on-budget. Analytical Program Management (APM) is a methodology, pioneered on highly complex NASA programs, for completely integrating cost, schedule and risk. APM allows projects to immediately determine the cost impacts of schedule growth and vice versa. This paper will present a case study of a large-scale NASA program, reviewing the process of establishing connected artifacts to yield powerful analytic insights for the project team. Through Monte Carlo simulation, the risk-adjusted cost estimate and schedule are generated to enable planning using statistical confidence levels. The APM methodology determines lead drivers of cost and schedule risk, as well as mechanisms for re-planning the program to ensure a more optimal outcome.