Applying Machine Learning on ABC-XYZ Inventory Model Using Multivariate and Hierarchical Clustering

DOI

10.2991/978-2-38476-132-6_30How to use a DOI?

Keywords

Inventory Management; Multivariate Clustering; Machine Learning

Abstract

Most of ventures need to manage many kinds of product urging them to prioritize one product on top of another. The prioritization criteria will depend on each department, making one product possibly get different priority level by different department. Unsupervised Machine Learning discipline could provide solution for this problem by using Hierarchical Clustering either Agglomerative or Divisive Clustering. This research uses a skincare company as case study which have 300 kinds of products to be managed and stored in 8 distributed warehouses. Each department recommend their own variables to be considered in classifying products from business aspect to nature of the products. Factors such as revenue contribution ranging from high-mid-low (ABC class) and demand volatility ranging from seasonal-linear-constant (XYZ class) making the clustering become multivariate. Using 4-years data, the algorithms have successfully classified product into multiple categories and mapped as matrix, where each product on the same box of matrix would be treated equally. Having the clustering established, each department would run business based on this classification, such as inventory placement in warehouse, prioritized product when purchasing or conducting promotion program. The implementation of this initiative on SME could be an inspire for other SMEs or even bigger company to implement the same methodology, concept, or model. This research presents how Machine Learning can be implemented in the Industry 5.0 with minimum effort and investment but has an impact on the companywide level. This research also promotes the use of data as the basis in decision-making and strategic planning processes, not using instinct, convention, or any form of irrational process.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Irvan Prama Defindal
AU  - Nopriadi Saputra
PY  - 2023
DA  - 2023/10/31
TI  - Applying Machine Learning on ABC-XYZ Inventory Model Using Multivariate and Hierarchical Clustering
BT  - Proceedings of the 6th International Conference on Vocational Education Applied Science and Technology (ICVEAST 2023)
PB  - Atlantis Press
SP  - 322
EP  - 334
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-132-6_30
DO  - 10.2991/978-2-38476-132-6_30
ID  - Defindal2023
ER  -