ANLY482 AY2016-17 T2 Group12 : Project Overview

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Project Background

KST Bikers currently gets feedback all the time. These feedbacks are large in volume and can range from track conditions to maintenance of KST Bikers' bicycles. In order to ensure that the bicycles, systems and tracks are maintained properly, the company has to act upon these feedbacks so as to resolve complaints or to improve upon problems that cyclists may face.

In order to improve on the current situation, KST Bikers intends to:

• To reduce in volume of feedback in order to increase manpower productivity
  

As there is a large volume of feedback, huge amount of manpower is needed to go through the feedbacks. If the volume of feedback is reduced, it would increase manpower productivity by assigning the manpower to more important tasks.

• Provide interactive dashboard for employees
  

KST Bikers are currently using excel and face many different challenges in conducting feedback analysis:

1. Time consuming for KST Bikers to manually clean the data and generate advanced data analysis
2. It is not intuitive to conduct visual analysis as many steps are required to generate the static charts

Project Motivation

Our team choose to take analytics as a second major because we believe it is a useful skill to learn for the future. We believe that any company should use analytics to improve their businesses as data would always tell us many interesting things that are happening.

What really motivates us in this project is that this project is dealing with something that we can relate to. This project is dealing with public feedback regarding cycling and one of the aims of this project is to reduce the amount of feedback. Singaporeans are by nature very willing to give feedback about various issues, especially about bicycles which is a means of transport that many locals use on daily basis. This is something that we are also very critical about. Hence, Singaporeans feel more appreciated when there are fewer problems about cycling and when their feedback about cycling is taken into account.

The three of us are not any different when it comes to giving feedback about problems that we feel needs to be improved. As a result, we are highly motivated to take on this project as firstly we feel that if we are able to reduce the volume of feedback, we could improve our fellow Singaporeans' well being as KST Bikers can utilize more manpower to tackle other critical issues. Secondly, if we can provide KST Bikers with a interactive dashboard. The employees will be analyse what category of feedback is the highest. This way the employees can figure out ways to implement measures to reduce feedback.

Project Objective

The initial objectives of the project is to:

• Discover the trends in the feedback data. The following are some examples, but not limited to:
  • Distribution of type of feedback
  • Relationship between various attributes (e.g. category, source and type of feedback) of new and recurring cases
  • Profiles of people who provide feedbacks
• Examine the external factors which generate feedbacks. The following are some factors, but not limited to:
  • Date: Which month would generate more feedback?
  • Weather conditions: What type of weather conditions would generate more feedback?
  • Major events: Do major events affect the volume of feedback generated?
  • Policy changes: Do policy changes affect the volume of feedback generated?
• Develop appropriate interactive visualizations to allow discovery of insights from various datasets

But after further exploratory data analysis and reviews with KST Bikers and supervisor, TSK Transporters have revised the objectives to the following:

• Observe meaningful insights in the feedback data

These insights would be used to help KST Bikers in understanding which feedback categories are causing the bulk of the feedback.

• Develop interactive visual dashboard

The interactive visual dashboard will be able provide KST Bikers with the following benefits:

1. Provides descriptive data analytics capabilities
2. Display user friendly interactive visualizations
3. Automatically generate visualizations for various trends, thereby saving time and resources
4. Automate data cleaning and processing upon upload of feedback data file to save time for employees

Scope of Work

The scope of the project includes the following:

• Discovery
  • Research on the business domain
  • Identify potential data sources
• Data Preparation
  • Data collection
  • Data cleaning
  • Data normalization and transformation
  • Initial data exploration
• Model Planning
  • Data exploration
• Model Building
  • Create interactive dashboards
  • Formulate insights and recommendations
• Communicate Results
  • Presentations to KST Bikers and Prof. Kam
  • Final Paper