Model-based Approach in Defense Portfolio Management: Data Preparation, Analysis, and Visualization of Decision Spaces

Abstract

The research team adapted a previously developed system-of-systems analytic workbench to address Integrated Acquisition Portfolio reviews via mission engineering analysis. The team illustrated the findings to date in developing decision-support tools tailored to the needs of these reviews and the insights they produce for improved acquisition outcomes. The essence of the prototype acquisition decision-support tools we are developing is a combination of portfolio optimization and mission engineering. We explore the interactions between candidate systems to acquire and existing systems to identify capability gaps and features of portfolios that optimally cover a family of mission threads. Moreover, we investigate the role of digital engineering in facilitating this process to shift the stakeholders’ mindset from the traditional forms of acquisition decision-making to a predominantly model-based approach, from data preparation, analysis, and visualization of the decision spaces. Preliminary findings indicate that these approaches indeed do provide the stakeholders with a broader range of more accessible information, such as resource tradeoffs and cost sensitivity analysis. Longer-term goals include a more comprehensive model-based acquisition decision-support system, with consistent data definitions extracted from “authoritative sources of truth,” thereby connecting all models with common data definitions.