Business Analytics in Excel: Optimization and Simulation

Every business faces complex decisions involving limited resources and unpredictable outcomes. Learning how to model these scenarios mathematically allows you to make data-driven decisions that minimize risk and maximize efficiency. This course guides you through the process of building robust decision-making models in Excel. You will transition from basic spreadsheet use to structuring optimization problems, running simulations to account for uncertainty, and applying modern analytical tools to solve resource allocation, logistics, and scheduling challenges. What you'll learn: - Understand the foundational concepts of business modeling, key terminology, and how to structure decision variables. - Configure Solver to find optimal solutions for resource allocation, assignment, and transportation problems. - Apply sensitivity analysis to evaluate how changes in assumptions impact your business outcomes. - Design simulations to model uncertainty and risk using probability concepts. - Leverage modern Excel features like dynamic arrays and modern formula patterns to streamline your analytical workflows. You will start with core analytical definitions and basic modeling structures before moving step-by-step through linear programming, optimization setups, and risk simulation. The material is presented through clear, written explanations and structured, text-based practice scenarios. This course is designed for aspiring analysts, business professionals, and spreadsheet users who want to build practical decision-making models. No prior background in advanced mathematics or programming is required. Start building smarter business models and optimizing your decision-making processes today.