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	The practicum’s project sponsor is a supply chain and logistics company. Currently, its warehouse data are not being utilized. By providing its warehouse data (inbound and outbound) transactions to the team, the sponsors would like the team to create a dashboard to help solve 3 main issues. Firstly, to help sponsor categorize warehouse SKUs into ABC categories (each category refers to how fast the goods move) to facilitate optimizing storage of SKUs in warehouse. Secondly, to provide employees with a high level visualization of the SKUs movement into, within, and out of the warehouse. Lastly, to analyze and suggest possible alternatives to improve the picking process within the warehouse (order picking VS batch picking).	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	Sugar is an interactive city guide that seeks to encourage a culture of exploration in Singapore and helping local small businesses get discovered. Sugar’s merchants are mainly small local businesses in Singapore. It has a large variety, including cafes, small restaurants, bars, hair salons, gyms, gift shops. The benefits for merchants is advertising to users that are in close proximity to them. Users in turn get discounts on products that are in the closest proximity to them. As Sugar is a relatively young startup in Singapore, it has not yet attained a critical mass of user and merchant numbers. As such, user growth and user experience is vitally important. To reach this critical mass, Sugar needs to minimise user and merchant attrition, and retain vital segments of both groups in order to preserve the network effect of Sugar’s platform. This is done via 3 means: Voucher Redemption User Retention Merchant Retention The objective of our project will be to understand user and merchant behavior via survival analysis, subsequently deriving recommendations for Sugar to increase its KPIs - voucher redemption rate, user retention rate and merchant retention rate.	Group02- Team TurnKEY Kang Long Elizabeth Tan Yi Sheng, Lim	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Benjamin Lee Founder and Chief Executive Officer of Sugar Technologies Pte Ltd.
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)	Media Research Consultants Pte Ltd
Social Media Analytics	The aim of this project is to provide deeper insight into SGAG's social network across its multiple platforms, namely Instagram and Twitter. Our client is the co-founder of the company and he seeks insights that can spur growth in SGAG's follower numbers. Through our analysis and research, we aim to help discover what kind of users are on each platform; the key engagement leaders for each topic; and how wide is the reach of these individuals. The final deliverables will aim to: Visualise the social networks of SGAG Identifying the user segments who engage SGAG's content, as filtered by topics and their reach	Group05- Team AP WANG Shyan Ann NG Tse Siong Sherman YONG Chin Wei	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Karl Mak, Co-founder at SGAG
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
Understanding Employee Social Networks	People analytics is a rapidly growing area of business intelligence and big data technology. It uses various facets of people-related data to optimize business outcomes and solve business problems. The application of people analytics with new techniques such as predictive behavioural analytics has helped organisations to save millions of dollars while improving attrition rates, employee engagement and identify underlying training requirements. TrustSphere is the widely recognized market leader in Relationship Analytics. TrustSphere enables forward thinking organizations to unlock the inherent value of their own networks using next generation technology. The solutions provide real-time intelligence and insights which help clients across the globe improve salesforce effectiveness, enterprise-wide collaboration and corporate governance.The motivation behind this project is to assist TrustSphere in verifying the effectiveness of their product through other statistical techniques. Access to TrustSphere’s datasets will allow the team to build a system from scratch using previously unused raw data to better understand turnover and attrition rules. The minimum research points we would like to address: Understand the number of relationships an employee will have at different periods of time in his or her working life Measure the speed of growth at which employee relationships grow in a company Correlations between the sizes of internal and external relationships employees have Through social network analysis, calculate the likelihood of an employee in an informal group leaving a company upon the exit of another closely tied employee Identification of metrics that can help predict the likelihood of an employee leaving	Group07- Team YSR Ridwan Ismeer Sadhvi Ilango Yashraj Jalota	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Greg Newman, Product Manager - TrustSphere
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
CodeBetter Analytics: Identifying Patterns in Learning	Students using a web portal to learn programming languages and frameworks will answer a series of questions, which have their timings and results recorded. An analytics dashboard will be built to read from a live Firebase, thus dynamically generating charts and information for students to view their progress. Course conductors may also use this dashboard to better understand the needs of their students and modify their course accordingly.	Group09 - KyuBI Shane GOH Ghee Gin Darren LIM Fei Hong LIM Wei Yang	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Prof. Chris Boesch Associate Professor of Information Systems (Education)
Urban Analytics for Planning Support System	The main aim of this project is to assess the walkability of a neighbourhood in Tampines. There are two parts to this project. The first part of the project involves analyzing the commuting patterns in Tampines using ez-link data. From there, we will identify a particular neighbourhood in Tampines to do a more in-depth walkability analysis on it which will form the second part of this project. The objectives of our project are: Part 1: Identify Commuter Patterns • To understand the demographics of the residents in Tampines • To analyze the commuting patterns in Tampines • To highlight areas where the time taken to travel by bus is longer than walking • To identify a particular area in Tampines for further analysis in the second part of the project Part 2: Identify Gaps in Infrastructure • To understand if the current physical infrastructures cater to the needs of the residents (based on demographics) • To analyze the connectivity of the selected residential area to the points of interests • To highlight areas in the selected residential area that are less accessible and propose recommendations to improve walkability	Group10- Team WalkThere Jeanne Sim Peh Wuen Lim Hui Ting Jaclyn Lim Hui Ting	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)
Uncovering Market-Insights for Charles & Keith	This project aims to help Charles & Keith gain a better understanding of its China market through the use of data-analytics. With the market insights gathered, provide recommendations for the business on how they may apply them to its business to positively affect consumer buying decisions and capture more market share within China. Key objectives of this project involves: Visualise the overall generic consumer purchasing patterns and behaviour within China Identify best-selling products and item set for different regions or tiers of cities Highlight the differences between transactions of different locations in terms of product specifications or types Some business areas where the project findings could be applied: Strategic placement of products within product catalogues In-store shelving decision Strategic marketing promotions to cross-sell and upsell, at a localized market level Suggest Market Basket Analysis algorithm solutions for C&K’s e-commerce site Data set includes sales transaction data from all of Charles & Keith’s stores in China.	Group11-Team AYE Audrey Jee Zhi Ying Edwin Tan Soon Hong Toh Yan Ying	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Charles & Keith Group
Health Promotion Board GIS Application	Our objective is to build an interactive and visual web application that utilises GIS functions for geospatial planning and analysis. It will be able to compute and analyse HPB KPI reporting metrics. The web application should be easy to use to support the staff both technical and non-technical in their many Health Promotion programmes and outreach planning. It will also assist the staff in clear and easy to understand presentations to the executives who have little or no background in GIS analysis so as to be able to plan their operations.	Group12 - Griffins Melissa Lim Seok Yu Tan Wei Liang Tan Yu Ling	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Health Promotion Board
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
Singapore Students Performance Analysis	This project makes use of PISA (Programme for International Student Assessment) data collected during the latest survey of 2012 with regards to Singapore. The aim of this project is to explore the relationship between computer usage in school and secondary-school student performance in reading and mathematics. Building on the current international work done by PISA, our project will bring the analysis to Singapore national level and study various aspects of students of performance relative to their access to computer in and outside of school, in order to provide insights for education policy makers of Singapore Ministry of Education (MOE).	Group15 Nguyen Le Hong Ngoc Poh Jin Hui Zhao Yazhi	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)
Car Park Overspill Study	Land Transport Authority(LTA) aims to do an analysis to understand the current parking situation at these selected locations. The LTA Contract Parking Study was awarded to Media Research Consultants in March 2015 to undertake the Study involving 65 car park locations in Singapore, including 30 retail malls, 15 retail and F&B clusters in landed housing estates, 10 hawker centres, and 10 community clubs. This study was to conduct parking occupancy surveys, human traffic counts, and interview surveys at the selected locations at stipulated times. The study incorporated the conventional method of manual counting as well as deployment of automated counting equipment. Face-to-face interviews were employed for the interview survey segment. In addition to the study and taking of detailed data from field surveys, this project aims to develop a simulation tool that enables the systematic analysis of the impacts of various parameters, using a collected set of quantifiable data.	Group16 Blackbox Chen Xueye Zeng Jiadong Zheng Wei	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Media Research Consultants Pte Ltd
Social Media Content Analysis	This project aims to uncover valuable insights on SGAG’s content attributes in order to achieve audience growth. Using data gathered from SGAG’s facebook page for the year 2015, the team hopes to firstly, conduct exploratory data analysis so as to identify overall performance trends. Next, the team will be performing cluster analysis followed by sentiment analysis, topic analysis and content analysis. Lastly, the team will be building a regression model, which includes findings derived from the analysis conducted, in order to predict better performing future posts. With the insights gained, the team will be providing recommendations to enable data driven content creation, thus allowing SGAG to achieve their aim of greater growth.	Group17 T(eam)ROLL Nur Amirah Bte Mohd Noor Gan Sze Huey	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Karl Mak, Co-founder at SGAG
Visualizing & Analyzing of Decision Making in a Connected World	The aim of this project is to help marketers from the FMCG industry to identify target consumer profiles, digital media platforms, and as well as devices to allow for more targeted marketing strategies, thus maximizing return on investment (ROI) on their business decisions. Our team will be developing an interactive and dynamic dashboard that will allow end users to visualize data findings and generate actionable insights through the data from the Connected Life study.	Group18 - Team VisCon Denise Quek Si Ying Tan Wei Song	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Subhashish Dasgupta, SEA Automotive and Regional Client Director at TNS
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
Gambling Behaviour Pattern Analysis	The aim of our project is to allow Singapore Pools to better understand the gambling behaviours of their customers through the identification of gambling patterns, which can be unique across different clusters of individuals. Each cluster might have their own specific ways of splitting their bets, different churn rates, preference for a league, different decision making process, and ways of selecting their winning bets per match. Such behavioural patterns could possibly be linked back to certain demographics pertaining to the cluster, allowing us to further infer reasons behind their gambling habits, and hopefully could help us identify those irresponsible gamblers. For the purpose of the project, the scope of our project is limited to the Sports Betting segment of their Account Customers. The objectives of our project: (1) Profile their existing pool of customers through clustering analysis (2) Create a data visualization of the consumer betting activity (3) Build a dashboard to visualize the profiling and data points	Group 20 - SMU Analytical Gambling Unit Ng Ngee Heng, Eugene Wilson Wong Pham Minh Khoa	Prof. Kam Tin Seong Associate Professor of Information Systems (Practice)	Singapore Pools