Difference between revisions of "ANLY482 AY2017-18T2 Group27 : Homepage"
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[[ANLY482 AY2017-18 Term 2 Projects | <font color="#262626" size=2><b>ANLY482 AY2017-18 T2 Projects</b></font>]] | [[ANLY482 AY2017-18 Term 2 Projects | <font color="#262626" size=2><b>ANLY482 AY2017-18 T2 Projects</b></font>]] | ||
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| + | <font color=#292929>Project Description</font></div> | ||
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| + | DHL is the largest logistics firm in the industry today and they currently operate in over 220 countries and regions. Their large size and global presence have allowed them to forge many corporate accounts with other companies. In this project, we will be focusing on the analysis of air freight data of a particular account with DHL. | ||
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| + | Effective account management is vital in ensuring optimal service level provided by DHL and customer satisfaction. Currently, DHL faces issues like tracking operational performance, forecasting shipment volume and spotting trends. These problems are especially pertinent to DHL as it implies that DHL is not optimizing their shipment cargo capacity and business procedure with each account. Despite having numerous datasets, DHL have not been actively utilizing it. Currently, DHL hopes to utilize data to gain insightful and actionable insights to target the problems mentioned above.By using Power BI and Python, we will perform an analysis on a account and lane level dataset. Through this, we aim to generate insights and trends pertaining to regional, sector and trade lane levels. Subsequently, these insights will be used by DHL monitor an account’s shipment behavior, conduct meaningful conversations with customers and better plan their capacity for peak seasons. | ||
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Revision as of 22:06, 14 January 2018
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Project Description
DHL is the largest logistics firm in the industry today and they currently operate in over 220 countries and regions. Their large size and global presence have allowed them to forge many corporate accounts with other companies. In this project, we will be focusing on the analysis of air freight data of a particular account with DHL. Effective account management is vital in ensuring optimal service level provided by DHL and customer satisfaction. Currently, DHL faces issues like tracking operational performance, forecasting shipment volume and spotting trends. These problems are especially pertinent to DHL as it implies that DHL is not optimizing their shipment cargo capacity and business procedure with each account. Despite having numerous datasets, DHL have not been actively utilizing it. Currently, DHL hopes to utilize data to gain insightful and actionable insights to target the problems mentioned above.By using Power BI and Python, we will perform an analysis on a account and lane level dataset. Through this, we aim to generate insights and trends pertaining to regional, sector and trade lane levels. Subsequently, these insights will be used by DHL monitor an account’s shipment behavior, conduct meaningful conversations with customers and better plan their capacity for peak seasons.
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