Decision trees enable businesses to quantify decision making by placing numerical values on potential outcomes of uncertain decisions. They allow comparison of different options by calculating the expected values based on estimated probabilities and outcomes. While useful, decision trees have limitations such as how accurate the underlying data and probability estimates are. The example shows a decision tree for a business considering opening a new outlet, with branches based on economic growth probabilities and monetary outcomes. Changing the probability estimates impacts the expected values and optimal decision.