Difference between revisions of "ANLY482 AY2017-18T2 Group10"

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==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em;  text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic';  border-left:8px solid #1b96fe; margin-bottom:5px"><font color= #000000><strong>Introduction</strong></font></div>==
 
==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em;  text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic';  border-left:8px solid #1b96fe; margin-bottom:5px"><font color= #000000><strong>Introduction</strong></font></div>==
 
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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. <br/><br/>
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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. <br/>
  
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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 food due to expiry, not enough space in storage, the inability to satisfy customer demand, etc. <br/><br/>
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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.  
  
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Our main objective is to forecast the number of ingredients needed for the next order cycle. This can be done by using Time series analysis to forecast weekly customer count and afterwards, predict inventory consumption by using Panel Data Analysis. Our business goal is to improve company’s business planning, decision-making, reduce food wastage and improve food freshness.
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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.
 
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==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em;  text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic';  border-left:8px solid #1b96fe; margin-bottom:5px"><font color= #000000><strong>Project Progress</strong></font></div>==
 
==<div style="background: #ffffff; padding: 17px;padding:0.3em; letter-spacing:0.1em; line-height: 0.1em;  text-indent: 10px; font-size:17px; text-transform:uppercase; font-weight: light; font-family: 'Century Gothic';  border-left:8px solid #1b96fe; margin-bottom:5px"><font color= #000000><strong>Project Progress</strong></font></div>==
 
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Revision as of 20:02, 14 April 2018

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HOME

ABOUT US

PROJECT OVERVIEW

ANALYSIS & FINDINGS

PROJECT MANAGEMENT

BACK TO MAIN ANLY482

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

1. Project proposal
 2. Interim Presentation
 3. Abstract Paper & Full Paper
 4. Final Paper Submission

  • Upcoming Events (This week)

1. AP Research Paper Presentation


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