Alessia Micelli
Cost Forecasting for Extended Warranty contracts Application to a real case study in the automotive sector.
Rel. Eliana Pastor. Politecnico di Torino, Master of science program in Mathematical Engineering, 2025
Abstract
In the era of Big Data many companies are relying on data-driven decisions to contribute to the achievement of business targets. One of the most challenging yet interesting challenges a company faces is the ability to adopt and develop increasingly competitive and innovative methodologies. The role of new technologies is to extract valuable knowledge and derive data-driven insights to enhance business performance. This thesis project deals with a topic of relevance to the automotive industry: Predictive Analytics, which has become a cornerstone of modern business strategy, enabling companies to anticipate future trends, optimize operations and make data-driven decisions. Specifically, the aim of the project is the development and implementation of predictive models in order to accurately forecast the end-of-life costs of Extended Warranty contracts, for vehicles used in agricultural and construction sectors.
Forecast analysis supports and improves the management of warranty contracts, by reducing maintenance costs and allocating funds for ongoing contracts effectively
Relators
Academic year
Publication type
Number of Pages
Additional Information
Course of studies
Classe di laurea
Aziende collaboratrici
URI
![]() |
Modify record (reserved for operators) |
