ANLY482 AY2017-18 T1 Group1: Project Management
For our analysis we have defined the following constraints: - As mentioned earlier, eatigo operates in 8 markets. We are currently discussing scoping this down with our project supervisor. - eatigo’s data has been recorded from 2013 onwards. However, the period for which we will receive the data depends on the markets which we scope down to.
For our project we will be progressing in phases as follows:
Phase 1: Understanding the Business Problem
We adopted the following methods to get a thorough understanding of the problem that eatigo is facing:
- Initial discussion with Eatigo’s Marketing and Data Science Team to understand the business model, booking statistics and user behavior
- Primary research by speaking to customers about their booking behaviour on eatigo
- Secondary research to understand people’s dining habits and further understand eatigo’s business model
Phase 2: Analysis Plan
After understanding the business problem, we worked on an initial analysis plan to identify the data sources required and generate our hypothesis. However this is subject to change as we progress with the project
Phase 3: Data Collection & Cleaning
Our sponsor will be directly sharing the data with us. However, presently we have not received the data as the NDA is still to be signed.
Phase 4: Derive insights
As mentioned, our initial steps upon receiving the data include data understanding, data cleaning, data exploration and data transformation.
Depending on the our findings from above, we will be deciding our next steps forward in terms of analytical & visualization techniques and software to use to derive insights
Phase 5: Recommendation
Based on our insights we will be developing a recommendation plan for Eatigo which will enable the company to not only optimize yield management by improving usage rates among current customers but also attract new vendors to their platform.
Work Plan:
We have prepared a work plan for our project as follows. This gantt chart will be reviewed after Week 2 once we receive our data, and week 3 once we consult our supervisor.
[Our discussions with the sponsor, professor and amongst ourselves ]
