Title

Predictive Analytics in Forecasting

Author(s) Information

Matthew Suarez, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Engineering

Department - Author 1

Industrial and Manufacturing Engineering Department

Degree Name - Author 1

BS in Industrial Engineering

Date

6-2017

Primary Advisor

Karla Carichner, College of Engineering, Industrial and Manufacturing Department

Abstract/Summary

Predicting future demand can be of tremendous help to businesses in scheduling and allocating appropriate amounts of material and labor. The more accurate these predictions are, the more the business will save money by matching supply with demand as closely as possible. The approach for an accurate forecast, and the goal of this project, involves using data analytics techniques on past historical sales data. Working with Campus Dining, a year's worth of their daily sales data will be analyzed and ultimately used for the end result of both an accurate forecasting technique and a way to display the results in a user friendly manner. The feasibility and effectiveness of doing so will be determined at the end of this project.

URL: https://digitalcommons.calpoly.edu/imesp/208