Difference between revisions of "ANLY482 AY2017-18T2 Group07"

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[[ANLY482_AY2017-18T2_Group07|<font color="#6FEBAO" size=3><font face= "Century Gothic"><b>HOME</b></font>]]
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[[G7_Project Overview | <font color="#00C6BB" size=2><font face= "Century Gothic"><b>PROJECT OVERVIEW</b></font>]]
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[[G7 Findings |<font color="#00C6BB" size=2><font face= "Century Gothic"><b>ANALYSIS & FINDINGS</b></font>]]
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[[G7 Project Management|<font color="#00C6BB" size=2><font face= "Century Gothic"><b>PROJECT MANAGEMENT</b></font>]]
[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>HOME</strong></font>]]
 
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[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>PROJECT OVERVIEW</strong></font>]]
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[[G7 About Us |<font color="#00C6BB" size=2><font face= "Century Gothic"><b>ABOUT US</b></font>]]
[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>PROJECT FINDINGS</strong></font>]]
 
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[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>PROJECT MANAGEMENT</strong></font>]]
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[[Main_Page |<font color="#00C6BB" size=2><font face= "Century Gothic"><b>PRACTICUM HOMEPAGE</b></font>]]
[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>DOCUMENTATION</strong></font>]]
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<center>Note: due to the confidential nature of this project, we shall refer to our Project Sponsor as the "Company X" throughout this wiki, and all other entity names have been anonymized. </center>
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Team Data Heavy Legends wants to help its sponsor provide its service in the most efficient manner possible by making sense of the data they currently have. Through our efforts we hope to satisfy all stakeholders involved equally.
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Project Sponsor
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The sponsor company is one of the world’s largest logistics companies (Company X). It provides international courier, parcel ad express mail services. With a vast global network which spans over 220 countries and territories, Company X has an inevitable need to establish and maintain strong relationships with its clientele.
  
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Within the Sponsor organization, the team has been directly liaising with Group Account Managers (GAM). A typical GAM manages the account of one Business Unit (BU) of a large client. The team aims to help GAMs get a better idea of the operational performance being delivered to the clients they are serving.  
[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>ABOUT US</strong></font>]]
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[[ANLY482_AY2017-18_T2_Group07|<font face ="Lucida Grande" color="#FFCC00"><strong>Practicum Homepage</strong></font>]]
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Research Objectives
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<li>To understand the difference between the operational performance across business units and flight types through suitable statistical tests </li>
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<li>To explore different visualizations in order to represent the results from the statistical tests used and provide a more comprehensive view </li>
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Latest revision as of 18:05, 15 April 2018

DHL Banner.png


HOME

 

PROJECT OVERVIEW

 

ANALYSIS & FINDINGS

 

PROJECT MANAGEMENT

 

ABOUT US

 

PRACTICUM HOMEPAGE


DHL tracker.PNG


Note: due to the confidential nature of this project, we shall refer to our Project Sponsor as the "Company X" throughout this wiki, and all other entity names have been anonymized.



Team Data Heavy Legends wants to help its sponsor provide its service in the most efficient manner possible by making sense of the data they currently have. Through our efforts we hope to satisfy all stakeholders involved equally.


Project Sponsor

The sponsor company is one of the world’s largest logistics companies (Company X). It provides international courier, parcel ad express mail services. With a vast global network which spans over 220 countries and territories, Company X has an inevitable need to establish and maintain strong relationships with its clientele. Within the Sponsor organization, the team has been directly liaising with Group Account Managers (GAM). A typical GAM manages the account of one Business Unit (BU) of a large client. The team aims to help GAMs get a better idea of the operational performance being delivered to the clients they are serving.

Research Objectives

  1. To understand the difference between the operational performance across business units and flight types through suitable statistical tests
  2. To explore different visualizations in order to represent the results from the statistical tests used and provide a more comprehensive view