Overview
We are developing analysis methodologies for recognizing risky projects. The project health can be diagnosed using project management perspectives and mathematical statistics from services sciences. Not just software quality, but also a broader perspective is being pursued to prevent seriously diseased of project statuses.
From project managers' answers, which may include subjective judgments about projects, our methodology extracts causal relationships among various factors based on multivariable analysis methods such as factor analysis and artificial neural network to diagnose the appropriateness of project mangers' input and forecast the project status.