Difference between revisions of "Teppei Syokudo - Improving Store Performance: Project Management"
| (4 intermediate revisions by the same user not shown) | |||
| Line 12: | Line 12: | ||
| style="background:none;" width="1%" | | | style="background:none;" width="1%" | | ||
| − | | style="padding:0.4em; font-size:100%; background-color:#000066; font-family:Book Antiqua; text-align:center; color:#E6E87D" width="17%" |[[Teppei Syokudo - Improving Store Performance: Evaluating Store KPIs |<font color="#ffffff" size=3><b> | + | | style="padding:0.4em; font-size:100%; background-color:#000066; font-family:Book Antiqua; text-align:center; color:#E6E87D" width="17%" |[[Teppei Syokudo - Improving Store Performance: Evaluating Store KPIs |<font color="#ffffff" size=3><b>Improving Store Performance</b></font>]] |
| style="background:none;" width="1%" | | | style="background:none;" width="1%" | | ||
| Line 30: | Line 30: | ||
<div style="margin:20px; padding: 10px; background: #ffffff; text-align:center; font-family: Trebuchet MS, sans-serif; font-size: 95%;-webkit-border-radius: 15px;-webkit-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96); -moz-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);"> | <div style="margin:20px; padding: 10px; background: #ffffff; text-align:center; font-family: Trebuchet MS, sans-serif; font-size: 95%;-webkit-border-radius: 15px;-webkit-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96); -moz-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);"> | ||
<font size =3 face=Georgia > | <font size =3 face=Georgia > | ||
| + | <p> Undergraduate Conference for Data Analytics Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | ||
| + | <p> Undergraduate Conference for Data Analytics Paper 2 - Improving Store Productivity in F&B store using Regression Models Submitted</p> | ||
<p> Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | <p> Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted</p> | ||
<p> Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted</p> | <p> Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted</p> | ||
| Line 43: | Line 45: | ||
<div style="margin:20px; padding: 10px; background: #ffffff; font-family: Trebuchet MS, sans-serif; font-size: 95%;-webkit-border-radius: 15px;-webkit-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96); -moz-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);"> | <div style="margin:20px; padding: 10px; background: #ffffff; font-family: Trebuchet MS, sans-serif; font-size: 95%;-webkit-border-radius: 15px;-webkit-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96); -moz-box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);box-shadow: 7px 4px 14px rgba(176, 155, 121, 0.96);"> | ||
<font size =3 face=Georgia > | <font size =3 face=Georgia > | ||
| − | <p>[[File: | + | <p>[[File:Timeline_v6.jpg|1475px]]</p> |
Latest revision as of 22:26, 17 April 2016
| Home | Product Portfolio Analysis | Improving Store Performance | Project Management | Documentation | The Team |
Current Progress
Undergraduate Conference for Data Analytics Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted
Undergraduate Conference for Data Analytics Paper 2 - Improving Store Productivity in F&B store using Regression Models Submitted
Final Paper 1 - Product Portfolio Management in F&B using Market Basket Analysis Submitted
Final Paper 2 - Evaluating and Establishing KPIs and Staff Performance in F&B store Submitted
Interim Report Submitted
Interim Wiki Updated
Timeline
Limitations and Assumptions
The greatest limitation and assumption that the team is currently working on is the integration of the data from the POS system and the current data obtained. Another limitation that the team faces is the availability and format of which the data is stored. Ideally with data of sales made by each transaction, the person making the sales should be recorded. If that information can be aggregated then we’d be able to more efficiently analyse staff productivity.
