This document discusses how predictive analytics can improve operational decisions and business outcomes. It provides examples of how predictive models can be applied to decisions around customer retention, campaign response, risk assessment, and fraud detection. The key challenges are effectively deploying models and ensuring analytics lead to concrete business actions. Decision management systems aim to address this by separating decision-making processes from operations and creating a closed loop between analytics and measurable results. The document advocates starting with high-impact decisions, engaging both business and IT stakeholders, and moving rapidly from predictions to actions through decision management.