Predicting warranty claims accurately to reduce the excessive cost incurred due to high inventory and hence improve Customer Experience.
One of the largest suppliers of automotive components was facing multiple issues due to inaccurate prediction of warranty repairs. This leads to bad customer experience. The client now wants to predict the claims to improve the customer experience.
The data sources were disparate and data quality was really poor. Hereby, in order to predict the claims, we cleaned and analyzed data to understand the underlying distributions and trends. The advanced quantitative approaches like Principal Component Analysis & Time Series Analysis were used to solve the problem.
The model helped in predicting the warranty claims accurately to meet the desired service levels and reduce the excessive cost incurred due to high inventory.
The overall cost saving for the year increased by 27%.
Proactive maintenance helped reduce warranty claims by 16%