This document discusses how teaching computers to think like decision makers can help bridge the gap between data/analytics and human decision making. It argues that while data/analytics are helpful, decision making requires modeling systems and understanding uncertainties, sensitivities, and risks. The document proposes "Decision Intelligence" software that would integrate data into computable systems models to help decision makers understand how different decisions may impact outcomes and risks. It envisions new types of visualizations that represent decision variables rather than just input data to provide insights on various decision scenarios.