ANLY482 AY2017-18T2 Group10
Introduction
Our sponsor is a food-service organisation that owns and manages various renowned restaurant brands. ABC Company has evolved into different concepts, with further overseas expansion. Under these concepts, the group has a total of 13 outlets in Singapore.
Currently, our sponsor is not able to accurately determine the number of ingredients to order for their chain of restaurants. It is often based on guesswork and gut feeling which has often led to excessive holding costs as well as food wastage and in some cases, shortage of ingredients. This is not ideal as it may lead to various issues such as cost due to the non-freshness of the product, throwing of expired food, insufficient storage space, and inability to satisfy customer demand.
Our first objective is to predict the number of ingredients needed for the next order cycle and create a model which they can use. With this model, the staff can more accurately gauge the optimal inventory quantity and order quantity and not need to rely on gut feeling from previous experience, as is the existing practice. In summary, our business goal is to ensure accurate and optimal orders to fulfil storage, optimising storage space for each individual outlet.
Our second objective is to forecast the weekly customer counts. 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
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- Upcoming Events (This week)
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