ANLY482 AY2017-18T2 Group10
Introduction
Our sponsor is a food-service organisation that owns and manages various renowned restaurant brands. XYZ Company has evolved into different concepts, with further overseas expansion. Under these concepts, the group has a total of 13 outlets in Singapore.
The food & beverage (F&B) industry is highly dependent on its customers for its success and sustainability. Being able to accurately forecast the number of customers patronising a restaurant allows the business to optimise their staff scheduling to provide the optimal customer service and experience and also allows the company to better plan inventory ordering. This should ultimately translate to improved revenue and lowered costs for the business.
To forecast the customer count for each of ABC company’s five outlets, we will perform a comparison of two time-series forecasting techniques – (1) exponential smoothing and (2) autoregressive integrated moving average (ARIMA), to determine the appropriate model to use.
Project Progress
- Project Completion Status
100% completed (estimate)
- Project Milestone
|
|
- Upcoming Events (This week)
|
1. AP Research Paper Presentation |
