Primary Author: Mr Graham Gilmer
Co-Author(s): Mr Eric Druker
Audience Focus: Intermediate
Application Type: Application
Venue: 2015 AACE International Annual Meeting, Las Vegas, NV, USA
Abstract: Cost, Schedule, and Risk integration remains a substantial challenge for the project management community. Despite the interconnection of these disciplines, it is rare when cost estimates/budgets, schedules, and risk registers are fully integrated artifacts. This lack of integration makes it impossible for leaders to make quick decisions to ensure programs are confident in finishing 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 case studies of large-scale programs and examine trends across government and commercial industries, reviewing the evolution of the APM process for 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.
Co-Author(s): Mr Eric Druker
Audience Focus: Intermediate
Application Type: Application
Venue: 2015 AACE International Annual Meeting, Las Vegas, NV, USA
Abstract: Cost, Schedule, and Risk integration remains a substantial challenge for the project management community. Despite the interconnection of these disciplines, it is rare when cost estimates/budgets, schedules, and risk registers are fully integrated artifacts. This lack of integration makes it impossible for leaders to make quick decisions to ensure programs are confident in finishing 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 case studies of large-scale programs and examine trends across government and commercial industries, reviewing the evolution of the APM process for 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.