ABSTRACT
Cost-volume-profit (CVP) analysis is a fundamental management accounting tool. Traditional analysis uses point estimates for model parameters and scenario analysis to forecast best-case and worst-case outcomes. This case extends prior teaching cases in several ways. Students use historical sales data to forecast both the mean and standard deviation of volume and price for the next year. Students are provided the forecasted cost parameters, along with steps and instructions to perform a Monte Carlo simulation in Python. Using Python for the simulation introduces them to, or reinforces their use of, a programming language frequently used in data analytics. The simulation enables them to grasp the notion, and quantify the impact, of uncertainty. Students produce visualizations consisting of time series plots of sales and histograms of the many CVP model outcomes. For instructors who prefer not to use Python, the case can also be completed using Excel.