Development of diagnostic analytics to maximize customer profitability in AC Logistics

AC Logistics Philippines helps customers establish a successful supply chain by tracking and controlling their shipments through its network. The company collaborates with numerous industries to create innovative, value-added solutions. The convergence of technology has transformed logistics competi...

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Main Author: Mangoma, Joseph D., Jr.
Format: text
Language:English
Published: Animo Repository 2022
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Online Access:https://animorepository.dlsu.edu.ph/etdm_infotech/10
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etdm_infotech-10112023-07-12T05:16:12Z Development of diagnostic analytics to maximize customer profitability in AC Logistics Mangoma, Joseph D., Jr. AC Logistics Philippines helps customers establish a successful supply chain by tracking and controlling their shipments through its network. The company collaborates with numerous industries to create innovative, value-added solutions. The convergence of technology has transformed logistics competitiveness, requiring flexibility. Thus, the company's tight partnerships with major airlines enable the most reliable and cost-effective air cargo solutions. The purpose of this capstone project is to develop diagnostic analytics to maximize customer profitability for AC Logistics in order to provide solutions to the company's problems, which include understanding what and why trends are occurring, aggregating data managed by different resources, and addressing errors in calculations by having set measures and calculated fields within the tool. The proponent used the CRISP-DM model which is flexible and iterative. In lieu of modelling, it is focused on data exploration and visualization to uncover insights on financial data trends. The proponent started with descriptive analytics to do diagnostics analytics. AC Logistics' data was visualized using visual vocabulary to present the appropriate visualization based on the company's needs and requirements. The results of the diagnostic analytics showed insights regarding which customers are profitable and the shipment commodity that generated the most profit. This has to lead the company to identify which customers to invest in. In addition, it has led to insights to handle operations during peak periods. The capstone project showed that customer profitability data, when properly used with descriptive and diagnostic analytics, provides insights that help the organization succeed financially. To enhance customer profitability, future studies should examine external variables such as flight, pandemic restrictions, seasonality, and inflation. Key Words: data analytics; air logistics; descriptive; diagnostic; seasonality 2022-12-02T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdm_infotech/10 Information Technology Master's Theses English Animo Repository Data mining Logistics Computer Sciences Data Science
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Data mining
Logistics
Computer Sciences
Data Science
spellingShingle Data mining
Logistics
Computer Sciences
Data Science
Mangoma, Joseph D., Jr.
Development of diagnostic analytics to maximize customer profitability in AC Logistics
description AC Logistics Philippines helps customers establish a successful supply chain by tracking and controlling their shipments through its network. The company collaborates with numerous industries to create innovative, value-added solutions. The convergence of technology has transformed logistics competitiveness, requiring flexibility. Thus, the company's tight partnerships with major airlines enable the most reliable and cost-effective air cargo solutions. The purpose of this capstone project is to develop diagnostic analytics to maximize customer profitability for AC Logistics in order to provide solutions to the company's problems, which include understanding what and why trends are occurring, aggregating data managed by different resources, and addressing errors in calculations by having set measures and calculated fields within the tool. The proponent used the CRISP-DM model which is flexible and iterative. In lieu of modelling, it is focused on data exploration and visualization to uncover insights on financial data trends. The proponent started with descriptive analytics to do diagnostics analytics. AC Logistics' data was visualized using visual vocabulary to present the appropriate visualization based on the company's needs and requirements. The results of the diagnostic analytics showed insights regarding which customers are profitable and the shipment commodity that generated the most profit. This has to lead the company to identify which customers to invest in. In addition, it has led to insights to handle operations during peak periods. The capstone project showed that customer profitability data, when properly used with descriptive and diagnostic analytics, provides insights that help the organization succeed financially. To enhance customer profitability, future studies should examine external variables such as flight, pandemic restrictions, seasonality, and inflation. Key Words: data analytics; air logistics; descriptive; diagnostic; seasonality
format text
author Mangoma, Joseph D., Jr.
author_facet Mangoma, Joseph D., Jr.
author_sort Mangoma, Joseph D., Jr.
title Development of diagnostic analytics to maximize customer profitability in AC Logistics
title_short Development of diagnostic analytics to maximize customer profitability in AC Logistics
title_full Development of diagnostic analytics to maximize customer profitability in AC Logistics
title_fullStr Development of diagnostic analytics to maximize customer profitability in AC Logistics
title_full_unstemmed Development of diagnostic analytics to maximize customer profitability in AC Logistics
title_sort development of diagnostic analytics to maximize customer profitability in ac logistics
publisher Animo Repository
publishDate 2022
url https://animorepository.dlsu.edu.ph/etdm_infotech/10
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