Difference between revisions of "ANLY482 AY2017-18 Term 2"
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<table class="wikitable centered" width="100%" color="blue"> | <table class="wikitable centered" width="100%" color="blue"> | ||
<tr> | <tr> | ||
− | <th | + | <th >Project Title</th> |
− | <th>About the Project</th> | + | <th >About the Project</th> |
− | <th | + | <th >Student Member(s)</th> |
− | <th | + | <th >Project Supervisor</th> |
− | <th | + | <th >Sponsor</th> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017- | + | <td>[[Image:Eatigo.png|center|250px|]] |
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group01 Know-Thy-Deals]</td> | ||
<td> | <td> | ||
Eatigo is an online restaurant reservation platform that serves to optimize restaurant capacity, by offering time-based discounts to manage demand. Operating on the principles of yield management, eatigo tries to help connect "empty tables" with "empty stomachs". Since its launch in 2013, eatigo has built a 2 million subscriber base. <br /> | Eatigo is an online restaurant reservation platform that serves to optimize restaurant capacity, by offering time-based discounts to manage demand. Operating on the principles of yield management, eatigo tries to help connect "empty tables" with "empty stomachs". Since its launch in 2013, eatigo has built a 2 million subscriber base. <br /> | ||
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<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group02 | + | <td> |
− | <td> | + | <center>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group02 Prediction and Test analytics for screening project applications on DonorsChoose.org]</center></td> |
+ | <td>DonorsChoose.org empowers public school teachers across the United States by giving them a platform to appeal directly to donors on the web to contribute toward the purchase of resources needed for classroom projects for their students. Through charitable crowdfunding, thousands of these requests are fulfilled each year to help bring classrooms to life. | ||
<br/> | <br/> | ||
− | + | As the number of project submissions is set to increase, DonorsChoose.org needs to find a way to scale the current screening process so that projects can be reviewed and posted as quickly as possible, while retaining consistency in the vetting process.</td> | |
<td> | <td> | ||
<b>Group 02 - Josh & Fried Investigations</b> | <b>Group 02 - Josh & Fried Investigations</b> | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>DonorsChoose.org </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[[Image:AY2017-18T2 Group03 Team Logo.png|center| | + | <td>[[Image:AY2017-18T2 Group03 Team Logo.png|center|250px|]] |
[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group03 OPTEAMIZATION] | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group03 OPTEAMIZATION] | ||
</td> | </td> | ||
− | <td> | + | <td>Our sponsor is a home-grown supply chain solutions company and leading regional supply chain management partner to a number of the world’s leading brands such as Dell, Motorola, Samsung, LG, Exxon Mobil, Unilever and Heinemann. The company has operations all over Asia Pacific, such as China, the whole of ASEAN, India and Korea and they service various industry segments: Chemicals & Healthcare, Consumers & Retail, Electronics & Technology, E-Commerce and Cold Chain. |
+ | |||
+ | A strong advocate for technological and operational innovation, the company advocates productivity and sustainability improvements through interactive solutions so that they can provide their diverse consumer-base from various industry clusters with world-class logistics services. With recent interest in an analytics, the company is now looking towards implementing analytical solutions to help manage their operational processes and improve the efficiency of operations with the help of technology. | ||
+ | As technology keeps improving, the company needs to stay ahead of their competition by staying relevant and efficient, so our group aims to help them by improving the operations of one of their clients by implementing a dashboard so that visualisations can be done automatically with minimal work from the operations head so that overtime hours can be better managed. | ||
+ | </td> | ||
<td> | <td> | ||
<b>Group 03</b> | <b>Group 03</b> | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>A Singapore-based Supply chain Management Company</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group04 Social Media Analytics with | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group04 Social Media Analytics with New Media Company]</td> |
− | <td> | + | <td>The company is a local news media and content distribution platform based in Singapore. The company was first started as a spin-off project of 9GAG to generate localized content in 2012. Unlike 9GAG which allows users to upload their self-generated content, or using content taken from other social media platforms, the sponsor produces and uploads its own original content. Their content is centered primarily around memes and issues that are relevant to young Singaporeans. |
− | To capture the interests of a wider audience, content generation is currently based on four strategies: relevance to audience, contains well-articulated stories, first to be published, and being unexpected. As of today, | + | To capture the interests of a wider audience, content generation is currently based on four strategies: relevance to audience, contains well-articulated stories, first to be published, and being unexpected. As of today, the company has approximately an audience size of 4 million per month across its platforms. |
− | However, | + | However, the company competes within a rapidly changing social media landscape where trends are short-lasting. It is therefore vital for the company to identify how to swiftly capture new trends and optimize their content for their targeted audience to attain a higher reach. This is relevant as the company's profitability is tied to its ability to effectively capture audience. Our project would strive to fulfill such goals by using analyzing their existing content published on their Facebook and YouTube channel. </td> |
<td> | <td> | ||
<b>Group 04</b> | <b>Group 04</b> | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>New Media Company</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group05 | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group05 Discovering Complexity Of Online Transactions Using Exploratory And Confirmatory Techniques: A Case Study Of Online Payment Gateway Provider In Singapore] </td> |
<td> | <td> | ||
− | + | With the growing trend of e-commerce, retailers have begun improving their online retail presence to boost sales and market share. This creates a need for reliable financial intermediaries to facilitate their online transactions. | |
− | + | ||
+ | This research paper aims to study the complexity of the online transactions carried out by our sponsor’s merchants, by gaining a deeper understanding of the transaction data and formulating recommendations to improve future decision-making. | ||
+ | |||
+ | In particular, we hope to assess the performance of the merchants, using number of approved transactions per merchant as a key performance indicator. Due to the different nature of businesses, our merchants vary in number of online transactions. As part of data preparation, we used interactive binning to categorize them. | ||
+ | |||
+ | To compare the performance of each merchants in each bin, we used a hybrid approach, merging characteristics of funnel plots with line of best-fit graphs. These graphs provided a better model fit to visualize merchants falling outside the 95% confidence interval. Such merchants are identified as Star and Laggard merchants. We also established a positive relationship between number of transactions and the number of approved transactions. | ||
+ | |||
+ | We then studied the characteristics of transactions carried out by the identified merchants. We used logistic fit to determine possible correlation between various independent variables and number of approved transactions. For any variable that has correlation, we used decision trees to map the expected approved-to-rejected transaction ratios. | ||
+ | |||
+ | Finally, we present a comprehensive discussion on the insights gained through data exploration. We also provide recommendations on how to set benchmarks for each merchant’s performance and improve the approved-to-rejected transaction ratio for merchants. | ||
</td> | </td> | ||
<td> | <td> | ||
− | <b>Group 05</b> | + | <b>Group 05 - Team R2Z</b> |
* Randolph Pang Hsieh Yi | * Randolph Pang Hsieh Yi | ||
* Ong Rui Zhi | * Ong Rui Zhi | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Online Payment Gateway Provider Company</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group06 Forex Currency | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group06 Technical Analysis and Time Series Forecasting of Price Movements for Forex Currency Pairs]</td> |
<td>pH7 is a private investment firm that serve clients who are keen to appreciate their wealth and grow their capital. With its expertise in trading of financial instruments and information analysis capabilities, it provides business solutions that are customised to their clients’ needs. Capitalising on cutting edge technology in their work, pH7 has been excelling in efficiency and professional. | <td>pH7 is a private investment firm that serve clients who are keen to appreciate their wealth and grow their capital. With its expertise in trading of financial instruments and information analysis capabilities, it provides business solutions that are customised to their clients’ needs. Capitalising on cutting edge technology in their work, pH7 has been excelling in efficiency and professional. | ||
<Br> | <Br> | ||
− | + | The ability to understand and visualize price movements of foreign exchange rates plays an important role in discovering insights for trading companies. Our client signed up with software companies and deployed their own data collection platforms for storing and accessing the latest exchange rate data to gain some insights on the movements of exchange rates. However, their brokerage provided dashboards do not deliver any combined analysis across more than one technical analysis model. Hence, they are interested to understand trends and price movements of currency pairs using technical analysis to enable them to better forecast and make more informed trade executions for their clients. <BR> | |
− | Hence, | + | <BR> |
− | + | Our group will be using technical analysis-Bollinger Bands, RelativeStrengthIndex and Time Series Forecasting- ARIMA method to analyze price movements and provide a form of trading action which they could adopt for USD/JPY currency pair. This would allow them to forecast future trends in the finance market and make more informed decisions in their trade executions. | |
<td> | <td> | ||
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<td>[http://ph7investment.com/ pH7 Investment]</td> | <td>[http://ph7investment.com/ pH7 Investment]</td> | ||
<td> | <td> | ||
− | |||
<tr> | <tr> | ||
− | |||
− | |||
<td> | <td> | ||
− | <b>Group 07</b> | + | <center><strong> |
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group07 STP+]</strong></center></td> | ||
+ | <td>Team DHL's client has been transforming worldwide logistics since 1969. From creating the International Air Express Industry, to giving flight to a parcel delivering drone, the client aims to connect people regardless of where they are. | ||
+ | <br> | ||
+ | Team Data Heavy Legends(DHL) wants to help its client provide its service in the most efficient manner possible. By developing Ship-to-Profile+ (STP+), an all-inclusive and interactive dashboard which correlates operational performance and ship to profile information, we aim to help our client's Group Account Managers(GAM) team produce higher value for all stakeholders alike, and to assist leaders in making more informed decisions. | ||
+ | </td> | ||
+ | <td> | ||
+ | [[Image:DHL_LOGO.png|center|250px|]] | ||
+ | <b>Group 07 - Data Heavy Legends</b> | ||
* Akshay Nayak | * Akshay Nayak | ||
* Rikin Khanna | * Rikin Khanna | ||
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<tr> | <tr> | ||
− | <td> | + | <td> |
− | <br>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group08 | + | <br>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group08 Indiscriminate Parking of Shared Bicycles in Singapore: Highlighting Operational Implications of Data Quality Issues and Analyzing a bike sharing companyoBike’s Responsiveness via Geospatial Analysis]</td> |
<td>Beginning their operations in January 2017, oBike is Singapore’s first homegrown stationless smart bicycle-sharing company which uses technology to change how transportation is viewed locally. oBike has bicycles located all over the island, and these bikes have built-in Bluetooth locks to enable one-way first and last mile commuting. This provides a convenient and environmentally friendly commute option for all, especially given Singapore’s compact size and interconnected urban areas. Despite intense competition stemming from other bicycle-sharing companies such as Mobike and OFO, oBike has achieved over one million downloads since its inception. Data has revealed that the company has consistently been at the top in terms of total number of application downloads, earning them the title of “Southeast Asia’s bike-sharing leader.” <br><br> However, in recent months, Singapore’s Land and Transport Authority (LTA) has issued new rules and regulations, requiring bicycles to be parked in designated yellow boxes around the islands. LTA enforcers survey the island, and issue tickets to bike-sharing companies in the event where bicycles are found to be illegal parked. From the time a ticket is issued, oBike has a mere four hours to move their illegally-parked bicycles. Failure to do so will incur hefty fines. Consequently, oBike’s current challenge is to manage illegal parking of their bicycles.</td> | <td>Beginning their operations in January 2017, oBike is Singapore’s first homegrown stationless smart bicycle-sharing company which uses technology to change how transportation is viewed locally. oBike has bicycles located all over the island, and these bikes have built-in Bluetooth locks to enable one-way first and last mile commuting. This provides a convenient and environmentally friendly commute option for all, especially given Singapore’s compact size and interconnected urban areas. Despite intense competition stemming from other bicycle-sharing companies such as Mobike and OFO, oBike has achieved over one million downloads since its inception. Data has revealed that the company has consistently been at the top in terms of total number of application downloads, earning them the title of “Southeast Asia’s bike-sharing leader.” <br><br> However, in recent months, Singapore’s Land and Transport Authority (LTA) has issued new rules and regulations, requiring bicycles to be parked in designated yellow boxes around the islands. LTA enforcers survey the island, and issue tickets to bike-sharing companies in the event where bicycles are found to be illegal parked. From the time a ticket is issued, oBike has a mere four hours to move their illegally-parked bicycles. Failure to do so will incur hefty fines. Consequently, oBike’s current challenge is to manage illegal parking of their bicycles.</td> | ||
<td> | <td> | ||
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<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group09 Koi Logistics Analysis]</td> | + | <td><center> [[Image:Fablogo.png|center|250px|]] |
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group09 Koi Logistics Analysis]</center> </td> | ||
<td> | <td> | ||
− | + | 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 along with data 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. | ||
</td> | </td> | ||
<td> | <td> | ||
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[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group10 Inventory Analytics for F&B Company]</td> | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group10 Inventory Analytics for F&B Company]</td> | ||
<td> | <td> | ||
− | Our sponsor is a food-service organisation that owns and manages various renowned restaurant brands. | + | 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. <br/> <br/> |
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/> | 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/> | ||
− | Our main objective is to forecast the number of | + | Our main objective is to forecast the weekly number of customers visiting each outlet and to help predict the monthly inventory consumption. With these models, 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. |
</td> | </td> | ||
<td> | <td> | ||
<b>Group 10 - TenneT</b> | <b>Group 10 - TenneT</b> | ||
− | * | + | * Lee Weng Ho Mervyn |
* Ong Ming Hao (Michael) | * Ong Ming Hao (Michael) | ||
* Wee De Rong Bryan | * Wee De Rong Bryan | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>ABC Company (Information Withheld)</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_11 Alleviating Operational Costs]</td> | + | <td><center> [[Image:T.W.O logo nobg.png | 200px ]] <br/> |
− | <td> | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_11 Alleviating Operational Costs] </center> </td> |
+ | <td> <p> Company ABC is a local SME within the logistic sector here in Singapore and is a typical example of a company that is currently facing problems maneuvering through its data to derive operational solutions. More specifically, Company ABC is facing an overarching problem of high operational costs which is primarily caused by un-optimized hiring in the various peak and erroneous filling process, which the team aims to solve through analytical approaches. </p><br/> <p>The team will be utilizing several key software and libraries, as well as taking into consideration the various limitations pertaining to the data, and ultimately aims to reduce the operational costs of Company ABC. Besides having short-term cost reductions, the company may also benefit from greater employee satisfaction and better brand reputation – which could potentially aid the company in achieving its long-term vision of expanding into other countries.</p> </td> | ||
<td> | <td> | ||
<b>Group 11 - T.W.O </b> | <b>Group 11 - T.W.O </b> | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Logistic Company ABC </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | |||
<td> | <td> | ||
− | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group12 ARTistique]</td> | |
+ | <td> | ||
+ | <div style="text-align:justify"> | ||
+ | ARTistique is a champion of the arts scene in Singapore. It offers a range of arts and cultural programmes and activities and seeks to nurture creative excellence. Through their programmes, ARTisque aims to support broad audience engagement and connect Singaporeans of all ages through the arts. | ||
+ | <br> | ||
+ | In supporting the arts scene, ARTistique has managed to quantify the qualitative in conducting a nation wide survey which captures sentiments and participation behaviours amongst Singaporeans. As such, with the initial buy-in towards data, ARTistique is interested in exploring the potential of their databank collection spanning the past decade. | ||
+ | </div> | ||
</td> | </td> | ||
<td> | <td> | ||
− | <b>Group 12</b> | + | <b>Group 12: Team Flair </b> |
* Aaron Poh Weixin | * Aaron Poh Weixin | ||
* Jia Min Leong | * Jia Min Leong | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td> ARTistique </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | |||
− | |||
<td> | <td> | ||
− | <b>Group 13 </b> | + | [[File:OPlytics Logo.png|300px|center]] |
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group13 Developing Human Resource Dashboards: A Case Study of a Logistic Processing Company in Singapore]</td> | ||
+ | <td>Logistics Company XYZ is a multinational logistics service provider focusing on packaging, storage and distribution of chemical industry products. As logistic solutions continue to be a driving force in today’s environment, Logistic Company XYZ strives to offer personalized solutions to its companies through in-house developments in advanced logistic and engineering technology. With zero tolerance to delays in order fulfilment, the company prioritizes efficiency and accuracy. To do so, the company is constantly looking for ways to adopt smart technology and centralized systems to improve the performance of its people and processes. | ||
+ | |||
+ | Since many of the company’s processes are inevitably labour and skill intensive, training and human development is a key focus in the company’s business strategy to ensure that its people are ready to handle the changing requirements needed to fulfil processes and orders present in today's competitive environment. | ||
+ | |||
+ | In this project, OP<big>+</big>lytics aims to propose targeted recommendations to minimize delays by investigating causes of delay in order fulfilment in the key processes identified and to address these causes related to the human factor through an analysis of employee training records and order fulfilment history. Lastly, OP<big>+</big>lytics aims to create a dashboard for the company to streamline the training required in its workforce while meeting job demands effectively.</td> | ||
+ | <td> | ||
+ | <b>Group 13: OP+lytics </b> | ||
* Chee Yixin Jerlyn | * Chee Yixin Jerlyn | ||
* Cheow Wan Ling Taffy Joan | * Cheow Wan Ling Taffy Joan | ||
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<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group14 | + | <td><center> |
+ | [[Image:Anly4821718T2G14Logo.png|center|130px|]] | ||
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group14 ReDeliver] | ||
+ | </center></td> | ||
<td> | <td> | ||
Logistic Company X is one of the world's greatest global market leader in the logistics industry. Company X commits its expertise in international parcel, express, air and ocean freight, road and rail transportation, contract logistics and international mail services to its customers. | Logistic Company X is one of the world's greatest global market leader in the logistics industry. Company X commits its expertise in international parcel, express, air and ocean freight, road and rail transportation, contract logistics and international mail services to its customers. | ||
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<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_15 | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_15 A Comparative Study on Visualization Platforms for the Dashboard Design of a Fast-Moving Consumer Goods Company in Singapore]</td> |
− | <td> | + | <td> Data visualization software is a powerful analytical tool. With the necessary data, an ideal set of visualizations helps businesses better understand their strengths, weaknesses, and performance against competitors, and make quicker and more effective business decisions. As a project team, we aim to improve our client’s data processing and analytics methods to improve their efficiency, provide clearer and more dynamic visualizations, and allow them to make improved marketing decisions. |
<br/> | <br/> | ||
</td> | </td> | ||
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<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td>[ | + | <td>[Company X]</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
<td> | <td> | ||
− | [[Image: | + | [[Image:Group_16_Logo.jpg|300px]] <br> |
− | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_16 Assessing success factors and impact of | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_16 Assessing success factors and impact of VWO A's programmes]</td> |
<td> | <td> | ||
− | As one of the biggest and most recognizable VWOs in Singapore, | + | As one of the biggest and most recognizable Voluntary Welfare Organisation VWOs in Singapore, our sponsor prides itself on being at the forefront of social innovation in the VWO landscape, with their programmes being fully subscribed to by organizations and individuals. Despite having a large reach across different target communities, they have not been able to accurately identify if they have truly made an impact on their beneficiaries, or their key success factors in their programmes. Hence, our project looks at their volunteer force, in order to see whether the beneficiaries are being adequately served. |
<br/> | <br/> | ||
</td> | </td> | ||
Line 305: | Line 341: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td> Voluntary Welfare Organisation (VWO) in Singapore </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_17 | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_17 Behavioral analysis of users from Database Request Log]</td> |
− | <td> | + | <td> |
+ | |||
+ | With over 250 000 e-books provided by both Lee Ka Shing (LKS) library and Kwa Geok Choo (KGC) law library through the web service at library.smu.edu.sg, SMU library provide an array of collections to cater to support teaching and research across the multiple schools and faculties. Currently, SMU library purchases e-books on certain databases through the Patron Driven Acquisition (PDA) scheme. The PDA scheme allows SMU library to list e-books that are not yet purchased as “available” to SMU community. These e-books are subsequently automatically purchase upon meeting some trigger points when access by the SMU community. At the moment, it has been highlighted that some e-book purchases are triggered by a single unique user due to repeated access. As a result, it diminishes the effective use of PDA funds as the e-books are not widely used across SMU community. | ||
+ | |||
+ | We aim to derive actionable insights from the data based on the behavioural patterns of users and understand the extent of effectiveness that PDA provides in meeting the needs of SMU community. | ||
+ | |||
+ | </td> | ||
<td> | <td> | ||
<b>Group 17</b> | <b>Group 17</b> | ||
Line 319: | Line 361: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>SMU Library</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[[Image: | + | <td>[[Image:TeamDAcctnew.png|300px]] |
− | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_18 | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_18 Using Multiple Linear Regression to Analyse Factors Affecting Costs Incurred for Cleaning Projects: A Case Study of a Cleaning and Conservancy Company in Singapore ]</td> |
− | <td> | + | <td> LS 2 Services Pte Ltd is a local cleaning and conservancy company that provides building cleaning services, landscape care and maintenance services activities in Singapore. For each prospective project site, costs incurred is estimated before tender is submitted. Expected costs incurred for each project has always been estimated based on the experience and professional judgement of its top management. However, such a method is not sufficient in cost-estimation as seen from several instances of loss-making projects. In this paper, we use multiple linear regression to build an explanatory model to find out what affects the various cost components incurred for conservancy project types. Explanatory variables such as dwelling units and commercial units converted to Equivalent Dwelling Units (EDU) are derived from identifying the facility descriptions of various project sites. The model being built for each cost component will help identify key possible cost drivers, as well as analyse whether an increase in any of the explanatory variables determined has an impact on manpower headcount as a cost driver. |
− | The | ||
</td> | </td> | ||
<td> | <td> | ||
Line 336: | Line 377: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>LS 2 Services Pte. Ltd. </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group19 | + | <td>[[Image:G19_Logo.png|center|250px|link=ANLY482 AY2017-18T2 Group19]] |
− | <td>This project aims to | + | <center>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group19 Library Course Reserve Materials Usage Analysis]</center></td> |
+ | <td>This project aims to analyze the usage volume, usage patterns and usage ratio of these course reserve materials over a period of time, and ultimately, be able to provide them insights into their collection policy.</td> | ||
<td> | <td> | ||
− | <b>Group 19 - | + | <b>Group 19 - LKS Bookbusters</b> |
* Joanne Ong Shi Ying | * Joanne Ong Shi Ying | ||
− | * | + | * Koh Wei De John |
* Rachel Tay | * Rachel Tay | ||
</td> | </td> | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Li Ka Shing Library</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group20 | + | <td>[[Image:Team20 Logo.jpg|300px]] |
− | <td> | + | <center>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group20 Team MaxiMuM]</center></td> |
+ | <td>We aim to optimise the online and offline resource availability in the library to maximise the learning effectiveness of SMU students. We further aim to analyse if usage patterns vary between students based on certain attributes like Programme, Year of Graduation and Education Level. This will help in develop actionable insights to alter current training and workshop methodology, search results on keywords and distributions channels of this content.</td> | ||
<td> | <td> | ||
<b>Group 20 - MaxiMuM</b> | <b>Group 20 - MaxiMuM</b> | ||
Line 370: | Line 413: | ||
<td>[[Image:AY1718 T2 Group21 Logo.png|center|200px|]] | <td>[[Image:AY1718 T2 Group21 Logo.png|center|200px|]] | ||
[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group21 Web Analytics for a Children's Education Company]</td> | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group21 Web Analytics for a Children's Education Company]</td> | ||
− | <td> | + | <td> Brainsmith is a children’s education company based in India that designs and delivers premium educational, learning products and content for early childhood learning and healthy brain development. Their products are targeted at families of higher economic standing with young children and besides having their own website to sell their goods and display their catalogue, they sell their products on various online e-commerce merchants and engages in digital marketing. Brainsmith has been operating for over a year but have conversion rates that are lower the industry average. With the data provided, we plan to use text analysis to identify incoming traffic patterns and clustering analysis to understand the customers’ navigation patterns on the website that leads to either purchases or exiting the website. </td> |
<td> | <td> | ||
<b>Group 21 - Shiksha </b> | <b>Group 21 - Shiksha </b> | ||
Line 383: | Line 426: | ||
<tr> | <tr> | ||
− | <td> | + | <td> |
[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_22 Freight Data Analysis]</td> | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_22 Freight Data Analysis]</td> | ||
− | <td> | + | <td> |
+ | This project aims to study into a critical factor behind XXX’s success as a freight transportation service provider: the price of its corporate shipping contracts. Contract bidding refers to the process of XXX submitting a tender to secure a corporate contract in order to provide its freight services to a company. To secure its shipping contracts, XXX has to go through several bidding rounds with competitors, which include major players such as UPS, Fedex and other companies in the same region. By discovering insights into the factors affecting the bidding price for its shipping contracts, this better allows XXX to understand the thought process and motivation behind the bidding results of its customers, across various industries as well as different countries, and potentially better prepares them for negotiation with their customers for future contract bidding rounds by offering better terms which are of greater concern specifically for different types of customers, thus enabling them to have a higher chance of earning contracts and reaping more profits. | ||
+ | </td> | ||
<td> | <td> | ||
− | <b>Group 22 - | + | <b>Group 22 - Freighters</b> |
* Teo Pei Sheng Nicholas | * Teo Pei Sheng Nicholas | ||
* Zhang Qian | * Zhang Qian | ||
Line 394: | Line 439: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>XXX</td> |
</tr> | </tr> | ||
+ | |||
+ | <td> | ||
+ | |||
+ | |||
+ | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2016-17_T2_Group23_Silver_Daisies Analysis on Medical Escort Transport Scheme]</td> | ||
+ | <td> | ||
+ | Our Sponsor provides programmes and services for the elderly and the sick, families, persons with disabilities, and children. | ||
+ | |||
+ | Our project focuses on their Medical Escort Transport (MET) service, which aims to transport homebound elders who are unable to attend medical appointments/treatments on their own and have no suitable or available caregiver to take them to their medical appointment/treatments. Despite being a meaningful initiative, the MET service currently faces profitability issues. Our project hopes to reduce operational costs and improve its efficiency so as to allow them to gain healthy surpluses. | ||
+ | </td> | ||
+ | <td> | ||
+ | '''Group 23 - Silver Daisies''' | ||
+ | * Carol Chong Siew Fang | ||
+ | * Loh Xiaoyou | ||
+ | * Tham Hin | ||
+ | </td> | ||
+ | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
+ | Associate Professor of Information Systems (Practice) | ||
+ | </td> | ||
+ | <td> XXX Medical Escort Transportation Provider | ||
+ | </td> | ||
<tr> | <tr> | ||
<td> [[File:REOLogo.png|200px|]] | <td> [[File:REOLogo.png|200px|]] | ||
<br/>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_24 REO]</td> | <br/>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_24 REO]</td> | ||
− | <td> | + | <td> REO is a leading property portal and geo-spatial search engine for Singapore properties through connecting demand and supply side of property market. REO has a subscription based model for commercial users to post and manage their property listings on their portal so its revenue is heavily reliant on its subscribers. To capture the growing demand and supply of the property market, REO needs to fully utilize its vast amount of collected data to increase engagement with its subscribers (commercial users). Our project would focus on analysing the data to increase engagement and creating visualisations to allow the staff to easily comprehend the data </td> |
<td> | <td> | ||
<b>Group 24 </b> | <b>Group 24 </b> | ||
Line 414: | Line 480: | ||
<tr> | <tr> | ||
<td>[[Image:ChopeLogo.png|center|200px|]] | <td>[[Image:ChopeLogo.png|center|200px|]] | ||
− | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_25 Improving Chope’s marketing campaigns | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_25 Improving Chope’s marketing campaigns through data analysis]</td> |
− | <td> Chope is a | + | <td> Chope is a Singapore-based restaurant reservation platform which connects diners to restaurants in real-time. In the past, restaurant reservations had to be made through phone calls, which could only be done during operating hours. Chope allows users to make instant reservations with zero booking or cancellation fees, with most of its revenue generated by charging restaurants fixed and per-diner fees for the use of its reservation system. With ambitions of becoming the dominant player in the region, Chope has been rapidly expanding in recent years and now serves over 2000 restaurants in Singapore, Hong Kong, Shanghai, Beijing, Jakarta and Bangkok. |
− | |||
− | |||
− | As consumers have | + | Most of the restaurant reservations on the Chope system are done via its website. Hence, the marketing channel utilised most by Chope is its Electronic Direct Mailer (EDM) to its user base, featuring content such as promotional deals, new restaurant additions and curated lists. As consumers have very varied preferences in the Food and Beverages industry, Chope hopes to improve the effectiveness of its EDM campaigns through better segmentation and personalisation with the help of analytical tools, which they believe would result in an increase in the number of reservations per user from the existing user base, translating directly to more revenue being generated. |
</td> | </td> | ||
Line 436: | Line 500: | ||
<td>[[Image:DataDiversLogo.png|center|200px|]] | <td>[[Image:DataDiversLogo.png|center|200px|]] | ||
[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group26 Geospatial Analysis for Branch Location Optimization]</td> | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group26 Geospatial Analysis for Branch Location Optimization]</td> | ||
− | <td> | + | <td>PQR is a Singapore based company with over 100 branches spread across Singapore as well as a growing online presence. They have a pronounced focused on providing aid to the community. Their employees are committed to helping the community albeit the elderly, challenged youth or the environment. The company itself, contributes over 60% of their profits to the betterment of the community each year. |
− | + | PQR has been facing a road block while deciding locations for their upcoming branches. They have conquered central Singapore and need a smarter method to filter out their possibilities. Our project will use location based data and find its relationship with the financial performance of PQR branches all over Singapore. Using this, we aim to find the optimal weightage of variables to supply them the company with, in order to find a location that is most in line with the client’s goals. | |
</td> | </td> | ||
<td> | <td> | ||
Line 447: | Line 511: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td> Company PQR </td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017- | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group27_%3A_Homepage Effective Dashboard Design for Business Decisions: A Case Study on Air Freight Business ]</td> |
− | <td> | + | <td> Company X is the largest logistics firm in the industry today and they currently operate in over 220 countries and regions. Their large size and global presence have allowed them to forge many corporate accounts with other companies. In this project, we will be focusing on the analysis of air freight data of a particular account with Company X. |
+ | Effective account management is vital in ensuring optimal service level provided by Company X and customer satisfaction. Despite having numerous datasets, Company X faces issues like tracking operational performance, forecasting shipment volume and spotting trends.By using Power BI, we will build an interactive dashboard to analyse commercial performance. Subsequently, these insights will be used by Company X monitor an account’s shipment behavior, conduct meaningful conversations with customers and better plan their capacity for peak seasons.</td> | ||
<td> | <td> | ||
− | <b>Group 27</b> | + | <b>Group 27 - KJS</b> |
* Sonea Kribaraja | * Sonea Kribaraja | ||
* Chew Pei En Jozanne | * Chew Pei En Jozanne | ||
Line 461: | Line 526: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Company X</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
<td> [[File:21 JMP logo.jpg|center|200px|]] | <td> [[File:21 JMP logo.jpg|center|200px|]] | ||
− | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_28 | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_28 Analysis of Southeast Asian Hub Ports] </td> |
<td> The Straits of Malacca are one of the world’s most important trade corridors and transshipment regions, accounting for one quarter of the world’s transshipments. Furthermore, the ASEAN region is one of the fastest growing marine trade routes, as it includes many countries with developed and developing maritime infrastructure. There are 3 important ports in the Strait of Malacca, Port of Singapore, Port Klang and Port Tanjong Pelepas. Our sponsor, operates port of Singapore, one of the world’s largest ports. | <td> The Straits of Malacca are one of the world’s most important trade corridors and transshipment regions, accounting for one quarter of the world’s transshipments. Furthermore, the ASEAN region is one of the fastest growing marine trade routes, as it includes many countries with developed and developing maritime infrastructure. There are 3 important ports in the Strait of Malacca, Port of Singapore, Port Klang and Port Tanjong Pelepas. Our sponsor, operates port of Singapore, one of the world’s largest ports. | ||
Line 485: | Line 550: | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_29 Byte Syzed]<br/> [[Image: | + | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_29 Byte Syzed]<br/> [[Image: Byteszed-new-logo.png|link=ANLY482_AY2017-18_T2_Group_29 |200px]] </td> |
− | <td> | + | <td> Our project sponsor, Erumpere, is a private company that aims to provide meaningful experiences to young children, between 4 to 12 years old. As the company grows, they have faced difficulties in managing their programmes and have had instances where there were too many camps that have been slotted in a week, which causes them to reschedule the programmes on another day because they did not have enough instructors to spread during that instance. The problem also extends to allocation of resources whereby there are insufficient resources and last minute problems that arise due to the lack of a proper management system to forecast the demands of the programmes. </td> |
<td> | <td> | ||
<b>Group 29 - Byte Syzed</b> | <b>Group 29 - Byte Syzed</b> | ||
Line 518: | Line 583: | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_31 | + | <td>[[File:Bannernew.png|center|250px|]] |
− | <td> | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18_T2_Group_31 Team Pedal On] |
+ | </td> | ||
+ | <td>Our sponsor is Singapore's first homegrown stationless smart bikesharing company which uses technology to change how transportation is viewed locally. It allows commuters to travel during one-way first and last mile commuting – via bicycles located all over the island. As the use of smart bike sharing becomes more prevalent, the number of indiscriminate parking is on the uprise too. There has been many notifications and fines issued by authorities like Land Transport Authority (LTA), Town Council and NParks regarding bike users not parking within the marked out yellow box. <br> | ||
+ | The project objective(s): <br> | ||
+ | 1. To identify where and when, indiscriminate parking is likely to occur so as to better manage the bikes before reports are made by citizens and government agencies. | ||
+ | 2. Focus on a specific area in Singapore to see how better optimization can be done on the allocation of bikes.</td> | ||
<td> | <td> | ||
<b>Group 31</b> | <b>Group 31</b> | ||
Line 528: | Line 598: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Bike-sharing Company</td> |
</tr> | </tr> | ||
<tr> | <tr> | ||
− | <td>[https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_32 | + | <td>[[File:Pharma G Logo.png|220px]] |
− | <td> | + | [https://wiki.smu.edu.sg/ANLY482/ANLY482_AY2017-18T2_Group_32 Interactive Visual Analytical Dashboard] |
+ | </td> | ||
+ | <td> | ||
+ | Pharma G is among the world's leading pharmaceutical firms manufacturing products for illnesses such as asthma, infections epilepsy and bipolar disorder in the form of medicines, vaccines and other various consumer health products. | ||
+ | |||
+ | With close to 100 brands of different medications under their belt and clients from the various medical sectors, it is an enormous challenge for anyone to monitor the performance of the sales of these products. Our sponsor wishes to be able to view and analyze the performance of her sales teams in order to provide a succinct business report to upper management. | ||
+ | |||
+ | Hence, this project aims to help the business better understand how the business has performed using an interactive data visualization dashboard. | ||
+ | </td> | ||
<td> | <td> | ||
<b>Group 32 </b> | <b>Group 32 </b> | ||
Line 542: | Line 620: | ||
<td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | <td>[http://sis.smu.edu.sg/faculty/profile/9618/KAM-Tin-Seong Prof. Kam Tin Seong] | ||
Associate Professor of Information Systems (Practice)</td> | Associate Professor of Information Systems (Practice)</td> | ||
− | <td> | + | <td>Pharmaceutical Company G</td> |
</tr> | </tr> | ||
</table> | </table> |
Latest revision as of 23:36, 16 April 2018
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|
Project Title | About the Project | Student Member(s) | Project Supervisor | Sponsor | |
---|---|---|---|---|---|
Know-Thy-Deals |
Eatigo is an online restaurant reservation platform that serves to optimize restaurant capacity, by offering time-based discounts to manage demand. Operating on the principles of yield management, eatigo tries to help connect "empty tables" with "empty stomachs". Since its launch in 2013, eatigo has built a 2 million subscriber base. |
Group 01 - sat@eatigo
|
Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | eatigo Pte. Ltd. | |
|
DonorsChoose.org empowers public school teachers across the United States by giving them a platform to appeal directly to donors on the web to contribute toward the purchase of resources needed for classroom projects for their students. Through charitable crowdfunding, thousands of these requests are fulfilled each year to help bring classrooms to life.
|
Group 02 - Josh & Fried Investigations |
Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | DonorsChoose.org | |
Our sponsor is a home-grown supply chain solutions company and leading regional supply chain management partner to a number of the world’s leading brands such as Dell, Motorola, Samsung, LG, Exxon Mobil, Unilever and Heinemann. The company has operations all over Asia Pacific, such as China, the whole of ASEAN, India and Korea and they service various industry segments: Chemicals & Healthcare, Consumers & Retail, Electronics & Technology, E-Commerce and Cold Chain.
A strong advocate for technological and operational innovation, the company advocates productivity and sustainability improvements through interactive solutions so that they can provide their diverse consumer-base from various industry clusters with world-class logistics services. With recent interest in an analytics, the company is now looking towards implementing analytical solutions to help manage their operational processes and improve the efficiency of operations with the help of technology. As technology keeps improving, the company needs to stay ahead of their competition by staying relevant and efficient, so our group aims to help them by improving the operations of one of their clients by implementing a dashboard so that visualisations can be done automatically with minimal work from the operations head so that overtime hours can be better managed. |
Group 03
|
Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | A Singapore-based Supply chain Management Company | ||
Social Media Analytics with New Media Company | The company is a local news media and content distribution platform based in Singapore. The company was first started as a spin-off project of 9GAG to generate localized content in 2012. Unlike 9GAG which allows users to upload their self-generated content, or using content taken from other social media platforms, the sponsor produces and uploads its own original content. Their content is centered primarily around memes and issues that are relevant to young Singaporeans.
To capture the interests of a wider audience, content generation is currently based on four strategies: relevance to audience, contains well-articulated stories, first to be published, and being unexpected. As of today, the company has approximately an audience size of 4 million per month across its platforms. However, the company competes within a rapidly changing social media landscape where trends are short-lasting. It is therefore vital for the company to identify how to swiftly capture new trends and optimize their content for their targeted audience to attain a higher reach. This is relevant as the company's profitability is tied to its ability to effectively capture audience. Our project would strive to fulfill such goals by using analyzing their existing content published on their Facebook and YouTube channel. |
Group 04
|
Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | New Media Company | |
Discovering Complexity Of Online Transactions Using Exploratory And Confirmatory Techniques: A Case Study Of Online Payment Gateway Provider In Singapore |
With the growing trend of e-commerce, retailers have begun improving their online retail presence to boost sales and market share. This creates a need for reliable financial intermediaries to facilitate their online transactions. This research paper aims to study the complexity of the online transactions carried out by our sponsor’s merchants, by gaining a deeper understanding of the transaction data and formulating recommendations to improve future decision-making. In particular, we hope to assess the performance of the merchants, using number of approved transactions per merchant as a key performance indicator. Due to the different nature of businesses, our merchants vary in number of online transactions. As part of data preparation, we used interactive binning to categorize them. To compare the performance of each merchants in each bin, we used a hybrid approach, merging characteristics of funnel plots with line of best-fit graphs. These graphs provided a better model fit to visualize merchants falling outside the 95% confidence interval. Such merchants are identified as Star and Laggard merchants. We also established a positive relationship between number of transactions and the number of approved transactions. We then studied the characteristics of transactions carried out by the identified merchants. We used logistic fit to determine possible correlation between various independent variables and number of approved transactions. For any variable that has correlation, we used decision trees to map the expected approved-to-rejected transaction ratios. Finally, we present a comprehensive discussion on the insights gained through data exploration. We also provide recommendations on how to set benchmarks for each merchant’s performance and improve the approved-to-rejected transaction ratio for merchants. |
Group 05 - Team R2Z
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Online Payment Gateway Provider Company | |
Technical Analysis and Time Series Forecasting of Price Movements for Forex Currency Pairs | pH7 is a private investment firm that serve clients who are keen to appreciate their wealth and grow their capital. With its expertise in trading of financial instruments and information analysis capabilities, it provides business solutions that are customised to their clients’ needs. Capitalising on cutting edge technology in their work, pH7 has been excelling in efficiency and professional.
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Group 06
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | pH7 Investment | |
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Team DHL's client has been transforming worldwide logistics since 1969. From creating the International Air Express Industry, to giving flight to a parcel delivering drone, the client aims to connect people regardless of where they are.
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Group 07 - Data Heavy Legends
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | [1] | |
Indiscriminate Parking of Shared Bicycles in Singapore: Highlighting Operational Implications of Data Quality Issues and Analyzing a bike sharing companyoBike’s Responsiveness via Geospatial Analysis |
Beginning their operations in January 2017, oBike is Singapore’s first homegrown stationless smart bicycle-sharing company which uses technology to change how transportation is viewed locally. oBike has bicycles located all over the island, and these bikes have built-in Bluetooth locks to enable one-way first and last mile commuting. This provides a convenient and environmentally friendly commute option for all, especially given Singapore’s compact size and interconnected urban areas. Despite intense competition stemming from other bicycle-sharing companies such as Mobike and OFO, oBike has achieved over one million downloads since its inception. Data has revealed that the company has consistently been at the top in terms of total number of application downloads, earning them the title of “Southeast Asia’s bike-sharing leader.” However, in recent months, Singapore’s Land and Transport Authority (LTA) has issued new rules and regulations, requiring bicycles to be parked in designated yellow boxes around the islands. LTA enforcers survey the island, and issue tickets to bike-sharing companies in the event where bicycles are found to be illegal parked. From the time a ticket is issued, oBike has a mere four hours to move their illegally-parked bicycles. Failure to do so will incur hefty fines. Consequently, oBike’s current challenge is to manage illegal parking of their bicycles. |
Group 08
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | oBike Asia Pte. Ltd. | |
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 along with data 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. |
Group 09
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | KOI Thé Singapore Pte Ltd | ||
Inventory Analytics for F&B Company |
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 food due to expiry, not enough space in storage, the inability to satisfy customer demand, etc. Our main objective is to forecast the weekly number of customers visiting each outlet and to help predict the monthly inventory consumption. With these models, 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. |
Group 10 - TenneT
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | ABC Company (Information Withheld) | |
![]() Alleviating Operational Costs |
Company ABC is a local SME within the logistic sector here in Singapore and is a typical example of a company that is currently facing problems maneuvering through its data to derive operational solutions. More specifically, Company ABC is facing an overarching problem of high operational costs which is primarily caused by un-optimized hiring in the various peak and erroneous filling process, which the team aims to solve through analytical approaches. The team will be utilizing several key software and libraries, as well as taking into consideration the various limitations pertaining to the data, and ultimately aims to reduce the operational costs of Company ABC. Besides having short-term cost reductions, the company may also benefit from greater employee satisfaction and better brand reputation – which could potentially aid the company in achieving its long-term vision of expanding into other countries. |
Group 11 - T.W.O
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Logistic Company ABC | |
ARTistique |
ARTistique is a champion of the arts scene in Singapore. It offers a range of arts and cultural programmes and activities and seeks to nurture creative excellence. Through their programmes, ARTisque aims to support broad audience engagement and connect Singaporeans of all ages through the arts.
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Group 12: Team Flair
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | ARTistique | |
Developing Human Resource Dashboards: A Case Study of a Logistic Processing Company in Singapore | Logistics Company XYZ is a multinational logistics service provider focusing on packaging, storage and distribution of chemical industry products. As logistic solutions continue to be a driving force in today’s environment, Logistic Company XYZ strives to offer personalized solutions to its companies through in-house developments in advanced logistic and engineering technology. With zero tolerance to delays in order fulfilment, the company prioritizes efficiency and accuracy. To do so, the company is constantly looking for ways to adopt smart technology and centralized systems to improve the performance of its people and processes.
Since many of the company’s processes are inevitably labour and skill intensive, training and human development is a key focus in the company’s business strategy to ensure that its people are ready to handle the changing requirements needed to fulfil processes and orders present in today's competitive environment. In this project, OP+lytics aims to propose targeted recommendations to minimize delays by investigating causes of delay in order fulfilment in the key processes identified and to address these causes related to the human factor through an analysis of employee training records and order fulfilment history. Lastly, OP+lytics aims to create a dashboard for the company to streamline the training required in its workforce while meeting job demands effectively. |
Group 13: OP+lytics
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Logistic Company XYZ | |
Logistic Company X is one of the world's greatest global market leader in the logistics industry. Company X commits its expertise in international parcel, express, air and ocean freight, road and rail transportation, contract logistics and international mail services to its customers.
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Group 14
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Logistic Company X | ||
A Comparative Study on Visualization Platforms for the Dashboard Design of a Fast-Moving Consumer Goods Company in Singapore | Data visualization software is a powerful analytical tool. With the necessary data, an ideal set of visualizations helps businesses better understand their strengths, weaknesses, and performance against competitors, and make quicker and more effective business decisions. As a project team, we aim to improve our client’s data processing and analytics methods to improve their efficiency, provide clearer and more dynamic visualizations, and allow them to make improved marketing decisions.
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Group 15
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | [Company X] | |
Assessing success factors and impact of VWO A's programmes |
As one of the biggest and most recognizable Voluntary Welfare Organisation VWOs in Singapore, our sponsor prides itself on being at the forefront of social innovation in the VWO landscape, with their programmes being fully subscribed to by organizations and individuals. Despite having a large reach across different target communities, they have not been able to accurately identify if they have truly made an impact on their beneficiaries, or their key success factors in their programmes. Hence, our project looks at their volunteer force, in order to see whether the beneficiaries are being adequately served.
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Group 16 - Village People
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Voluntary Welfare Organisation (VWO) in Singapore | |
Behavioral analysis of users from Database Request Log |
With over 250 000 e-books provided by both Lee Ka Shing (LKS) library and Kwa Geok Choo (KGC) law library through the web service at library.smu.edu.sg, SMU library provide an array of collections to cater to support teaching and research across the multiple schools and faculties. Currently, SMU library purchases e-books on certain databases through the Patron Driven Acquisition (PDA) scheme. The PDA scheme allows SMU library to list e-books that are not yet purchased as “available” to SMU community. These e-books are subsequently automatically purchase upon meeting some trigger points when access by the SMU community. At the moment, it has been highlighted that some e-book purchases are triggered by a single unique user due to repeated access. As a result, it diminishes the effective use of PDA funds as the e-books are not widely used across SMU community. We aim to derive actionable insights from the data based on the behavioural patterns of users and understand the extent of effectiveness that PDA provides in meeting the needs of SMU community. |
Group 17
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | SMU Library | |
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LS 2 Services Pte Ltd is a local cleaning and conservancy company that provides building cleaning services, landscape care and maintenance services activities in Singapore. For each prospective project site, costs incurred is estimated before tender is submitted. Expected costs incurred for each project has always been estimated based on the experience and professional judgement of its top management. However, such a method is not sufficient in cost-estimation as seen from several instances of loss-making projects. In this paper, we use multiple linear regression to build an explanatory model to find out what affects the various cost components incurred for conservancy project types. Explanatory variables such as dwelling units and commercial units converted to Equivalent Dwelling Units (EDU) are derived from identifying the facility descriptions of various project sites. The model being built for each cost component will help identify key possible cost drivers, as well as analyse whether an increase in any of the explanatory variables determined has an impact on manpower headcount as a cost driver. |
Group 18 - Team DAcct
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | LS 2 Services Pte. Ltd. | |
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This project aims to analyze the usage volume, usage patterns and usage ratio of these course reserve materials over a period of time, and ultimately, be able to provide them insights into their collection policy. |
Group 19 - LKS Bookbusters
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Li Ka Shing Library | |
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We aim to optimise the online and offline resource availability in the library to maximise the learning effectiveness of SMU students. We further aim to analyse if usage patterns vary between students based on certain attributes like Programme, Year of Graduation and Education Level. This will help in develop actionable insights to alter current training and workshop methodology, search results on keywords and distributions channels of this content. |
Group 20 - MaxiMuM
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | SMU Libraries Analytics and Research Department | |
Web Analytics for a Children's Education Company | Brainsmith is a children’s education company based in India that designs and delivers premium educational, learning products and content for early childhood learning and healthy brain development. Their products are targeted at families of higher economic standing with young children and besides having their own website to sell their goods and display their catalogue, they sell their products on various online e-commerce merchants and engages in digital marketing. Brainsmith has been operating for over a year but have conversion rates that are lower the industry average. With the data provided, we plan to use text analysis to identify incoming traffic patterns and clustering analysis to understand the customers’ navigation patterns on the website that leads to either purchases or exiting the website. |
Group 21 - Shiksha
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Children's Education Company | |
Freight Data Analysis |
This project aims to study into a critical factor behind XXX’s success as a freight transportation service provider: the price of its corporate shipping contracts. Contract bidding refers to the process of XXX submitting a tender to secure a corporate contract in order to provide its freight services to a company. To secure its shipping contracts, XXX has to go through several bidding rounds with competitors, which include major players such as UPS, Fedex and other companies in the same region. By discovering insights into the factors affecting the bidding price for its shipping contracts, this better allows XXX to understand the thought process and motivation behind the bidding results of its customers, across various industries as well as different countries, and potentially better prepares them for negotiation with their customers for future contract bidding rounds by offering better terms which are of greater concern specifically for different types of customers, thus enabling them to have a higher chance of earning contracts and reaping more profits. |
Group 22 - Freighters
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | XXX | |
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Our Sponsor provides programmes and services for the elderly and the sick, families, persons with disabilities, and children. Our project focuses on their Medical Escort Transport (MET) service, which aims to transport homebound elders who are unable to attend medical appointments/treatments on their own and have no suitable or available caregiver to take them to their medical appointment/treatments. Despite being a meaningful initiative, the MET service currently faces profitability issues. Our project hopes to reduce operational costs and improve its efficiency so as to allow them to gain healthy surpluses. |
Group 23 - Silver Daisies
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Prof. Kam Tin Seong
Associate Professor of Information Systems (Practice) |
XXX Medical Escort Transportation Provider | |
![]() REO |
REO is a leading property portal and geo-spatial search engine for Singapore properties through connecting demand and supply side of property market. REO has a subscription based model for commercial users to post and manage their property listings on their portal so its revenue is heavily reliant on its subscribers. To capture the growing demand and supply of the property market, REO needs to fully utilize its vast amount of collected data to increase engagement with its subscribers (commercial users). Our project would focus on analysing the data to increase engagement and creating visualisations to allow the staff to easily comprehend the data |
Group 24
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Real Estate Online (REO)
[Sanitised] |
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Improving Chope’s marketing campaigns through data analysis | Chope is a Singapore-based restaurant reservation platform which connects diners to restaurants in real-time. In the past, restaurant reservations had to be made through phone calls, which could only be done during operating hours. Chope allows users to make instant reservations with zero booking or cancellation fees, with most of its revenue generated by charging restaurants fixed and per-diner fees for the use of its reservation system. With ambitions of becoming the dominant player in the region, Chope has been rapidly expanding in recent years and now serves over 2000 restaurants in Singapore, Hong Kong, Shanghai, Beijing, Jakarta and Bangkok.
Most of the restaurant reservations on the Chope system are done via its website. Hence, the marketing channel utilised most by Chope is its Electronic Direct Mailer (EDM) to its user base, featuring content such as promotional deals, new restaurant additions and curated lists. As consumers have very varied preferences in the Food and Beverages industry, Chope hopes to improve the effectiveness of its EDM campaigns through better segmentation and personalisation with the help of analytical tools, which they believe would result in an increase in the number of reservations per user from the existing user base, translating directly to more revenue being generated. |
Group 25
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | The Chope Group Pte. Ltd. | |
Geospatial Analysis for Branch Location Optimization | PQR is a Singapore based company with over 100 branches spread across Singapore as well as a growing online presence. They have a pronounced focused on providing aid to the community. Their employees are committed to helping the community albeit the elderly, challenged youth or the environment. The company itself, contributes over 60% of their profits to the betterment of the community each year.
PQR has been facing a road block while deciding locations for their upcoming branches. They have conquered central Singapore and need a smarter method to filter out their possibilities. Our project will use location based data and find its relationship with the financial performance of PQR branches all over Singapore. Using this, we aim to find the optimal weightage of variables to supply them the company with, in order to find a location that is most in line with the client’s goals. |
Group 26 - Data Divers
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Company PQR | |
Effective Dashboard Design for Business Decisions: A Case Study on Air Freight Business | Company X is the largest logistics firm in the industry today and they currently operate in over 220 countries and regions. Their large size and global presence have allowed them to forge many corporate accounts with other companies. In this project, we will be focusing on the analysis of air freight data of a particular account with Company X. Effective account management is vital in ensuring optimal service level provided by Company X and customer satisfaction. Despite having numerous datasets, Company X faces issues like tracking operational performance, forecasting shipment volume and spotting trends.By using Power BI, we will build an interactive dashboard to analyse commercial performance. Subsequently, these insights will be used by Company X monitor an account’s shipment behavior, conduct meaningful conversations with customers and better plan their capacity for peak seasons. |
Group 27 - KJS
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Company X | |
Analysis of Southeast Asian Hub Ports | The Straits of Malacca are one of the world’s most important trade corridors and transshipment regions, accounting for one quarter of the world’s transshipments. Furthermore, the ASEAN region is one of the fastest growing marine trade routes, as it includes many countries with developed and developing maritime infrastructure. There are 3 important ports in the Strait of Malacca, Port of Singapore, Port Klang and Port Tanjong Pelepas. Our sponsor, operates port of Singapore, one of the world’s largest ports.
Expanding a port’s capacity requires a large capital outlay. Furthermore, Singapore incurs a high opportunity cost due to its landmass constraints. Therefore, capacity planning is important to ensure that the port achieves a high utilization rate and maximizes its profit potential. Through this study, we hope to gain insights into the operation of these ports, and then use their respective strengths and weaknesses to formulate relevant operational strategies. |
Group 28 - 21 JMP SPREADSHEET
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | PSA Corporation Limited | |
Byte Syzed![]() |
Our project sponsor, Erumpere, is a private company that aims to provide meaningful experiences to young children, between 4 to 12 years old. As the company grows, they have faced difficulties in managing their programmes and have had instances where there were too many camps that have been slotted in a week, which causes them to reschedule the programmes on another day because they did not have enough instructors to spread during that instance. The problem also extends to allocation of resources whereby there are insufficient resources and last minute problems that arise due to the lack of a proper management system to forecast the demands of the programmes. |
Group 29 - Byte Syzed
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Erumpere | |
XYZ Web hosting company is an independent media publisher that focuses on travel and lifestyle stories for Singaporeans. They give locals trusted hyper-local information on what to do in and out of their country. This is done through their website, YouTube channel, Facebook page and Instagram. Their website is one part editorial based and one part community based where members can upload their own reviews and have their say about everything Singapore. Today, XYZ Web hosting company reaches over 3 million Singaporeans each month. |
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | XYZ Web hosting company | ||
Our sponsor is Singapore's first homegrown stationless smart bikesharing company which uses technology to change how transportation is viewed locally. It allows commuters to travel during one-way first and last mile commuting – via bicycles located all over the island. As the use of smart bike sharing becomes more prevalent, the number of indiscriminate parking is on the uprise too. There has been many notifications and fines issued by authorities like Land Transport Authority (LTA), Town Council and NParks regarding bike users not parking within the marked out yellow box. The project objective(s): |
Group 31
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Bike-sharing Company | ||
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Pharma G is among the world's leading pharmaceutical firms manufacturing products for illnesses such as asthma, infections epilepsy and bipolar disorder in the form of medicines, vaccines and other various consumer health products. With close to 100 brands of different medications under their belt and clients from the various medical sectors, it is an enormous challenge for anyone to monitor the performance of the sales of these products. Our sponsor wishes to be able to view and analyze the performance of her sales teams in order to provide a succinct business report to upper management. Hence, this project aims to help the business better understand how the business has performed using an interactive data visualization dashboard. |
Group 32
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Prof. Kam Tin Seong Associate Professor of Information Systems (Practice) | Pharmaceutical Company G |