Authors :
Hakizimana Alain; Dr. Wilson Musoni
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
https://tinyurl.com/4csc5ebw
Scribd :
https://tinyurl.com/syyn6tkf
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24FEB1099
Abstract :
This paper presents a novel approach to
optimize business inventory management through the
integration of ABC-XYZ analysis with advanced
machine learning models. Inventory management plays a
critical role in the operational efficiency and profitability
of businesses across various industries. Traditional
methods such as ABC analysis and XYZ analysis have
been widely used to classify inventory items based on
their importance and demand variability. However, the
effectiveness of these methods can be further enhanced
by leveraging machine learning techniques to analyze
historical data and make accurate predictions. In this
study, we propose a framework that combines ABC-XYZ
analysis with machine learning algorithms to classify
inventory items and optimize inventory control policies.
We demonstrate the effectiveness of our approach
through a case study conducted on a real-world business
dataset, highlighting significant improvements in
inventory turnover, cost reduction, and customer
satisfaction.
Keywords :
ABC-XYZ Analysis, Inventory Management, Machine Learning, Optimization, Business Efficiency.
This paper presents a novel approach to
optimize business inventory management through the
integration of ABC-XYZ analysis with advanced
machine learning models. Inventory management plays a
critical role in the operational efficiency and profitability
of businesses across various industries. Traditional
methods such as ABC analysis and XYZ analysis have
been widely used to classify inventory items based on
their importance and demand variability. However, the
effectiveness of these methods can be further enhanced
by leveraging machine learning techniques to analyze
historical data and make accurate predictions. In this
study, we propose a framework that combines ABC-XYZ
analysis with machine learning algorithms to classify
inventory items and optimize inventory control policies.
We demonstrate the effectiveness of our approach
through a case study conducted on a real-world business
dataset, highlighting significant improvements in
inventory turnover, cost reduction, and customer
satisfaction.
Keywords :
ABC-XYZ Analysis, Inventory Management, Machine Learning, Optimization, Business Efficiency.
