ANLY482 AY2017-18T2 Group07

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PROJECT OVERVIEW

ANALYSIS & FINDINGS

PROJECT MANAGEMENT

ABOUT US

PRACTICUM HOMEPAGE

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.

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

Our sponsor company is one of the worlds largest logistics companies providing international courier, parcel and express mail services. They have a vast global network which spans over 220 countries and territories, and establishing and maintaining relationships with its clientele is key. Our sponsor, the Group Innovation Strategy(GSI) department functions as 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.

Objectives

Our team wants to help the sponsor make better sense of their data. During this preliminary stage, we intend to achieve the following:

1. Data cleanup:
   • Inconsistencies in the data, for example- a text input in a numeric column
   • Missing values in the data
2. Exploratory Data Analysis:
   • Basic exploratory analysis to check skews in the data and identify general trends
   • Identify the bottlenecks in the shipment journey affecting the operational performance
   • Analyze the shipment patterns and trends for lane-wise pairs in the existing dataset

After the initial round of EDA, our team concluded that to help our sponsor in a sustainable manner, it’ll be essential to develop a visualization tool that encapsulates all key datasets.