ANLY482 AY2017-18 Group9: Project Overview
PROJECT BACKGROUND
KOI is one of the most well-known bubble tea brands in Singapore, founded in 2006. Despite this, it is facing logistics problems in their daily operations such that employees in different branches have difficulty predicting the right amount of ingredients to order.
Moreover, space constraints of each branch is different and have to be taken into consideration, since not every branch can order the same amount of quantity, leading to a steep learning curve for new employees.
Current employees also do not fully understand how much ingredients would be needed during promotional periods of certain products.
As such, our project aims to focus on predictive analysis tools such as multinomial regression models, along with data (e.g. sales, shipment, promotion details) provided by KOI to better understand correlations between different factors and sales, helping employees make better informed decisions on how much to order in the future.
PROJECT MOTIVATION
PROJECT OBJECTIVES
Our team will focus on correlations between different factors such as promotions, sales, shipment etc. and how these affect sales during different seasons of the year.
STAKEHOLDERS
Project Supervisor: Prof Kam Tin Seong, Associate Professor of Information Systems; Senior Advisor, SIS (Programme in Analytics)
Project Sponsor: Kyle Huang and Joshua Wong, Project Management Office, KOI THÉ Singapore Pte. Ltd
