Overfitting is a term primarily used in data science and machine learning, but it has a potent analogy in business leadership. In data science, overfitting occurs when a model is excessively complex and captures noise in the dataset as if it were a significant pattern. Similarly, in business leadership, overfitting happens when leaders make decisions based on too many insignificant variables, leading to suboptimal strategies and actions.