Data-Driven Monetization of Acquisition Risk

Abstract

The current state of practice in program risk assessment relies on the best judgment of program management and systems engineering to identify and qualitatively assess the nature and probability of risks. While there are best practices and lessons learned upon which the risk assessment process can rely, the process is still heavily qualitative and is performed by program management and systems engineering staff that are inherently optimistic about program success. As a result, risks and their consequences are frequently underestimated. We propose a methodology that actively collects, and continuously and quantitatively analyzes, metrics that are earlier indicators of risk than cost and schedule slips. This methodology includes the application of web-based technologies for collection and analysis, a quantified risk cloud and monetized risk thresholds, establishing a readily accessible knowledge base of previous program failures, and new metrics to be collected closer to the source of risk.