ANLY482 AY2015-16 Term 2

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List of Projects

Title	Analytics Practicum Description	Student Member(s)	Project Supervisor	Sponsor
Optimizing Warehouse Processing	Today, a local multi-national corporation faces the same adversity as many others – the plight of unworked data. Visualizations of the data provided by their in-house warehousing solution has proven to be difficult and much of the information is not placed to better use. The company hopes to solve 3 main issues, namely how they should categorize their warehouse supplies into ABC categories (each category refers to how fast the goods move) to store their goods in the best location available, how can their data be visualized better so that it is easier for employees to see, and how can their warehouses be utilized to the fullest to ensure minimal wastage. Our team, Skulptors, will be developing a dashboard application to solve the issues of this company. Control charts will be used to depict control of the movement of the SKUs, identifying which type of products have excessive or lack of movements from the warehouse. Treemaps will be used to identify products or SKUs that have minimal utilization of warehouses, and also to identify which warehouse location is not fully utilized. Java add-ons will be used to facilitate additional functions, such as allowing the upload of an excel file to update the database. This allows for our solution to remain sustainable. Time series line graphs will also be used for easy display of inflow and outflow rate of specified SKUs.	Group01- Team Skulptors LEONG Junkang, Gabriel TAN Siying ZHOU Xuanyi	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	A local multi-national corporation (MNC) Mr Khoo, Head of Operation Innovation & Development (Corporate) Miss Shen, Executive, Operations Innovation & Development (Corporate) Mr Sundar, Process Improvement Executive (Automation)
Analysis of User and Merchant Dropoff for Sugar App	To be confirmed	Group02- Team TurnKEY Kang Long Elizabeth Tan Yi Sheng, Lim	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Teppei Syokudo - Improving Store Performance	Teppei Syokudo is a Japanese Food and Beverage chain, under the umbrella of the famous Teppei Japanese Restaurant. In order to drive store performance through controllable factors, Teppei Syokudo is looking at focusing on staff performance. Most F&B businesses, including Teppei Syokudo, do not set detailed KPIs to evaluate how their staff are performing. If Teppei Syokudo is able to track the performance of their staff through relevant KPIs, they will be able to motivate staff to meet these KPIs, which will in turn boost the business’ bottom line.Teppei Syokudo has identified the following KPIs to assess their staff: Percentage of drinks sales (number of drinks sold / number of meals sold) a measurement of how hard the staff are up-selling Labour Productivity (sales $ / working hours) a measurement of how effective the shop manager is in staffing the shop However, the business is uncertain if these are the right KPIs to set. Also, if they are the right ones, they are unsure as to what would be a good target to meet. Another factor for driving store performance is through product portfolio mix. Even though the staff may be up-selling and cross-selling, they may not know the right products to cross-sell to increase the probability of the customer making additional purchases. For example, most customers may tend to purchase Drink X together with Don X. In this case, if a customer orders Don X and is about to make payment, the staff can suggest Drink X to the customer, hence prompting a higher probability for the customer to purchase Drink X.	Group03- Team APSM TAN Jhun Boon YAP Jessie OH Peng Ho	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Itaru Nagao, Managing Director YCP Management Southeast Asia Pte. Ltd. YCP Retailing SEA Pte. Ltd.
Car Park Overspill Study	The objective of this project is to assist Media Research Consultants Pte Ltd (MRC) in understanding the current parking situations in 65 different locations in Singapore. These 65 parking locations compromise of 30 retail malls, 15 retails and Food & Beverage (F&B) clusters in landed housing estates, 10 hawker centers, and 10 community clubs.	Group04- Team ATOM Macus KHOO JunHao YAN ShaoHong Chris YO Wee King	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
To be confirmed	To be confirmed	Group05- Team AP WANG Shyan Ann NG Tse Siong Sherman YONG Chin Wei	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Skyscanner Content Analysis	The project aims to help with Skyscanner's analyse its content sites in order to facilitate better planning. It will help understand the factors that affect content performance. Deliverables include creating a dashboard with visualizations that will help Skyscanner team to track the performance of articles across weeks and months, matched to trends and seasonality. It will be used to validate some of the intuitions they might have about certain content topics/types and to determine the best time to publish them. The dashboard will benchmark certain metrics against pageviews as well as additional attributes that Skyscanner does not currently analyse via Google Analytics, such as the impact of title, text length, theme of article and number of images. The team will also analyse content pages to determine what differentiates good and bad content based on certain performance metrics. This will be done through Text Mining (Topic Analysis), Content Crawling, MLR and matching with Google Trends API. Data set includes data from Skyscanner websites for the Singapore, Malaysia and Thailand markets.	Group06- Team SkyTrek Aseem PRABHAT Jedaiah TAN Jia Le NGUYEN Viet Huy	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Ms. Antoinette Tan Content Manager, APAC Skyscanner
To be confirmed	To be confirmed	Group07- Team YSR Ridwan Ismeer Sadhvi Ilango Yashraj Jalota	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Health Analytics	To build a web application that utilises GIS functions for geospatial planning and analysis. This application aims to facilitate the computation and analysis of Health Promotion Board (HPB) KPI reporting metrics. The insights generated from the application will be used to manage Health Promotion Programme and Outreach Planning.	Group08 - Team HealthTics Erwin Trinh Hiep Dang Khoa Nyein Su Aye	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Health Promotion Board
To be confirmed	To be confirmed	Group09 - Team WeiDaSha Shane GOH Ghee Gin Darren LIM Fei Hong LIM Wei Yang	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Urban Analytics for Planning Support System	In conjunction with a government initiated project - Re-imagining Tampines, this project aims to analyse the liveability of Tampines based on the connectivity between each residential blocks to the nearby facilities that are within walking distance. Site visits will be conducted to measure the actual distances taken to travel to the nearby facilities using a mobile application by QGIS called MapIt! Together with the demographic data provided by the sponsor, we aim to analyse how residential areas in Tampines are well-served to the public, as well as provide recommendations to our analysis and observations to improve connectivity in the area, thereby promoting walking to the residents.	Group10- Team WalkThere Jeanne Sim Peh Wuen Lim Hui Ting Jaclyn Lim Hui Ting	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
To be confirmed	To be confirmed	Group11-Team AYE Audrey Lee Zhi Ying Edwin Tan Soon Hong Toh Yan Ying	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Health Analytics	To be confirmed	Group12 - Griffins Melissa Lim Seok Yu Tan Wei Liang Tan Yu Ling	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Natasha Studio	To analyse the purchasing behaviour of Natasha Studio’s customers and provide sales and marketing recommendations.	Group13 Team Ameilax Sng Ei Leen Wong Jia Wei Tan Ziling Amy	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Larry Liu, Business Manager Natasha Studio
Marketing Analytics at Tokio Marine	To develop a database analysis to formulate a demographic and psychographic profile of Tokio Marine's customers	Group14- Team HEW Huai Zher Elijah Tan Yi Rong Winston Ong Bing Shen	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Benito Mable Vice President, New Opportunities Tokio Marine Asia
KTPH Public Health	The project is part of an ongoing effort to adopt data visualization to monitor public health by KTPH. Based on data from health screening and KTPH alignment programs, a dashboard can be constructed to assist health officers of KTPH to observe public health conditions, single out unhealthy individuals, and monitor their health progress. Additionally, the dashboard serves as a means to evaluate effectiveness of KTPH alignment programs to improve public health, and provide insights that can refine these programs to better target the population in future. As a follow-up of an IS480 project by team Cinquefoil, the aim is to improve the KTPH dashboard by adopting a richer set of visualization techniques, so as to enable a more user-centric data querying and discovery process. Specifically, KTPH users will be able to use the dashboard to identify unhealthy individuals of the population, the areas they are in, take appropriate actions and monitor the results of such actions As such, the objectives of our analytics project consist of the following: To visualize effectively the current health condition of the public across various regions of Singapore To allow health officers to track the health progress of individual at risks To assist health officers in monitoring the penetration rate of KTPH alignment programs targeted at the general public To allow users to interact with visualizations, thereby forming their own query and arriving at their own findings	Group15 Nguyen Le Hong Ngoc Poh Jin Hui Zhao Yazhi	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Khoo Teck Puat Hospital & SMU T-Lab
Car Park Overspill Study	To be confirmed	Group16 Blackbox Chen Xueye Zeng Jiadong Zheng Wei	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
To be confirmed	To be confirmed	Group17 T(eam)ROLL Nur Amirah Bte Mohd Noor Gan Sze Huey	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
To be confirmed	To be confirmed	Group 18 Denise Quek Si Ying Tan Wei Song	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed
Inpatient Meals Survey	To be confirmed	Group19 Pooja Tulsyan Akshat Agarwal	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Jason Soriano MRC Mediacorp
To be confirmed	To be confirmed	Group20 Ng Ngee Heng, Eugene Wilson Wong Pham Minh Khoa	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	To be confirmed