👉 Executives often use mathematical models to forecast financial performance, optimize resource allocation, and manage risk. They apply regression analysis to understand relationships between variables like sales and marketing spend, employing probability distributions (e.g., normal, Poisson) to predict outcomes and assess uncertainties. Optimization techniques, such as linear programming, help maximize profits or minimize costs under constraints like budget limits. Statistical tools like hypothesis testing and confidence intervals guide strategic decisions, ensuring choices are data-driven and aligned with business goals. These methods transform complex financial data into actionable insights, balancing precision with practicality to navigate market volatility and drive growth.
