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

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<center>Note: due to the confidential nature of this project, we shall refer to our Project Sponsor as the "Sponsor" throughout this wiki. We will not be able to publish major findings and any visualization or graphics made in line with this measure.</center>
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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. We will not be able to publish major findings and any visualization or graphics made in line with this measure.</center>
 
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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.
  
Our sponsor company is one of the worlds largest logistics companies providing international courier, parcel and express mail services.  
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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.  
 
 
Our sponsor is the consulting arm of this logistics company. It aims to improve operational efficiency across multiple business accounts to ensure that the Group Account Managers (GAM) are successfully able to increase value across their stakeholders.  
 
 
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Motivation
 
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Objectives
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Research Objectives
 
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Our team aims to help the GAMs make better sense of their data. During this preliminary stage, we achieved the following:<ol>
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<li>Flagged Inconsistent Entries -
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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>
  <li>Identified inconsistencies in the data, for example- a text input in a numeric column</li>
 
  <li>Identified missing values in the data</li>
 
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<li>Explored the data -
 
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  <li>Basic exploratory analysis to check skews in the data and identify general trends</li>
 
  <li>Identify the bottlenecks in the shipment journey affecting the operational performance</li>
 
  <li>Analyze the shipment patterns and trends for lane-wise pairs in the existing dataset</li>
 
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Revision as of 12:51, 15 April 2018

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Note: due to the confidential nature of this project, we shall refer to our Project Sponsor as the "Company X" throughout this wiki. We will not be able to publish major findings and any visualization or graphics made in line with this measure.



Team Data Heavy Legends(DHL) 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