Descriptive Analytics to Diagnose Operational Efficiency of Finished Vehicle Transport in the Automotive Industry

This paper shows use of descriptive analytics to solve the challenges of information about outsourcing transportation costs in finished vehicle logistics within a multi-channel network. The case study was conducted in the distribution area; they did not have information about outsourcing transportation costs. The proposal is to control transportation outsourcing costs using descriptive analytics and an interactive dashboard, use data over four months, the value of descriptive analytics, and KPI monitoring enables data-driven decision making to secure a better management of fleet management.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.174
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Descriptive Analytics to Diagnose Operational Efficiency of Finished Vehicle Transport in the Automotive Industry

Susana Casy Téllez-Ballesteros, Ricardo Torres-Mendoza, Erick Fernando Ruiz-Casas
Procedia Computer Science
Supply Chain Resilience and Risk Management
article

Descriptive Analytics to Diagnose Operational Efficiency of Finished Vehicle Transport in the Automotive Industry

Susana Casy Téllez-Ballesteros, Ricardo Torres-Mendoza, Erick Fernando Ruiz-Casas
article en

Abstract

This paper shows use of descriptive analytics to solve the challenges of information about outsourcing transportation costs in finished vehicle logistics within a multi-channel network. The case study was conducted in the distribution area; they did not have information about outsourcing transportation costs. The proposal is to control transportation outsourcing costs using descriptive analytics and an interactive dashboard, use data over four months, the value of descriptive analytics, and KPI monitoring enables data-driven decision making to secure a better management of fleet management.

Procedia Computer ScienceVol. 277
Universidad Nacional Autónoma de México (MX)
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Supply Chain Resilience and Risk Management
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