For most companies, data-driven decision making improves output and productivity, which leads to increased revenue. Data for decision making means using both real-time and historical data to inform decisions in the present. Today’s computational capabilities enable data scientists to put large sets of historical data to use. Complex situational modeling that uses these large datasets can help forecast outcomes and game scenarios. Hybrid decision making helps us put insights from data into action and illustrates how “data sight” helps us see things we could not see before. In combination with our other decision-making skills and tools, data sight improves a problem’s granularity, depth, and time horizon in extraordinary ways.