College of Engineering
Industrial and Manufacturing Engineering Department
BS in Industrial Engineering
Nianpin Cheng, Lecturer
This report focuses on developing a solution to a current problem faced at Julian’s Cafe and Bistro. The problem is that inaccurate order quantities are leading to inventory shortage and surplus which is causing unnecessary profit loss. After accessing and analyzing historical sales data, several forecasts were created using various approaches. After assessing each method and applying a mean absolute percentage error to see how accurate the forecasts were, the seasonal forecast with removing outliers initially was the selected method. After, this method was used to forecast the top three selling items at Julian’s and make demand predictions for busy times during the quarter versus non-busy time. The forecast for the coming year and the predictions can be used by the supervisor at Julian’s to make quicker and more accurate ordering decisions.