Level:
Advanced
TCM Section(s):
3.3. Investment Decision Making
Venue: 2022 AACE International Conference & Expo
Abstract: Within the National Nuclear Security Administration (NNSA), federal program managers heavily rely on their contractors at Department of Energy (DOE) laboratories to plan their budget. Each site is asked to prioritize investments internally and communicate those priorities back to the program offices. Federal program managers must weigh competing priorities across all laboratories to make funding decisions. In the NNSA, program managers often wish to eliminate the most risk, which raises the question: “how can the enterprise ensure it is using its dollars to buy down the most amount of risk?”
In this study, the author delivers an analytical approach to create optimal budget scenarios. Using linear programming, an operations research technique, the team is able to mathematically derive the “optimal” way to spend dollars on the recapitalization of programmatic equipment. Combining the risk score and the procurement cost for each piece of equipment, it is possible to translate this business question into a system of linear inequalities. Methods explored in this study do not provide a proposed budget for federal program managers. Instead, they facilitate a data-driven discussion between managers and laboratories. This process will enable federal program managers to make portfolio-wide decisions in an informed manner.
TCM Section(s):
3.3. Investment Decision Making
Venue: 2022 AACE International Conference & Expo
Abstract: Within the National Nuclear Security Administration (NNSA), federal program managers heavily rely on their contractors at Department of Energy (DOE) laboratories to plan their budget. Each site is asked to prioritize investments internally and communicate those priorities back to the program offices. Federal program managers must weigh competing priorities across all laboratories to make funding decisions. In the NNSA, program managers often wish to eliminate the most risk, which raises the question: “how can the enterprise ensure it is using its dollars to buy down the most amount of risk?”
In this study, the author delivers an analytical approach to create optimal budget scenarios. Using linear programming, an operations research technique, the team is able to mathematically derive the “optimal” way to spend dollars on the recapitalization of programmatic equipment. Combining the risk score and the procurement cost for each piece of equipment, it is possible to translate this business question into a system of linear inequalities. Methods explored in this study do not provide a proposed budget for federal program managers. Instead, they facilitate a data-driven discussion between managers and laboratories. This process will enable federal program managers to make portfolio-wide decisions in an informed manner.