Inventory Management for Slow Moving and High Volatility Items
Inventory management is an essential operation in the supply chain, owing to its strategic importance in supporting item availability and business continuity. The demand for slow-moving items is fundamentally ambiguous compared to demand for traditional fast-moving items due to the irregular demand...
| Main Authors: | , |
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| Format: | Other |
| Language: | en_US |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/1721.1/130970 |
| _version_ | 1811072117408530432 |
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| author | Efendigi, Esat Cameron, Kristin Katharine |
| author_facet | Efendigi, Esat Cameron, Kristin Katharine |
| author_sort | Efendigi, Esat |
| collection | MIT |
| description | Inventory management is an essential operation in the supply chain, owing to its strategic importance in supporting item availability and business continuity. The demand for slow-moving items is fundamentally ambiguous compared to demand for traditional fast-moving items due to the irregular demand pattern of slow-moving items, which causes forecasting problems. Under these circumstances, companies choose to stock more inventory than needed to mitigate the risk of insufficient inventory levels for business continuity and the high service level requested by the customers. Our capstone sponsor Optimas, a distributor of fasteners, requires an inventory policy playbook for low-volume, high-volatility items for its customers with a high service level. Higher inventory levels cause unnecessary spending of working capital. We aimed to define the best inventory level for each active, slow-moving item with this capstone project after analyzing the intermittent demand of the last four years. The whole slow-moving portfolio was categorized according to order quantities per year. We used Croston’s Method and hybrid periodic review (R,s,S) policy for items in Class A, which are the most frequently ordered within the past year. For Classes B and C, we used statistical methods and periodic review (R,S) policies. The output of this process is a list of items along with the recommended inventory level, the current inventory position, and the quantity to order per item. The results show that using these recommendations, Optimas can save up to 50% of their total inventory cost while maintaining their customers’ required service level. |
| first_indexed | 2024-09-23T09:01:10Z |
| format | Other |
| id | mit-1721.1/130970 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:01:10Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | mit-1721.1/1309702021-06-17T03:37:37Z Inventory Management for Slow Moving and High Volatility Items Efendigi, Esat Cameron, Kristin Katharine Demand Planning Inventory Management Inventory management is an essential operation in the supply chain, owing to its strategic importance in supporting item availability and business continuity. The demand for slow-moving items is fundamentally ambiguous compared to demand for traditional fast-moving items due to the irregular demand pattern of slow-moving items, which causes forecasting problems. Under these circumstances, companies choose to stock more inventory than needed to mitigate the risk of insufficient inventory levels for business continuity and the high service level requested by the customers. Our capstone sponsor Optimas, a distributor of fasteners, requires an inventory policy playbook for low-volume, high-volatility items for its customers with a high service level. Higher inventory levels cause unnecessary spending of working capital. We aimed to define the best inventory level for each active, slow-moving item with this capstone project after analyzing the intermittent demand of the last four years. The whole slow-moving portfolio was categorized according to order quantities per year. We used Croston’s Method and hybrid periodic review (R,s,S) policy for items in Class A, which are the most frequently ordered within the past year. For Classes B and C, we used statistical methods and periodic review (R,S) policies. The output of this process is a list of items along with the recommended inventory level, the current inventory position, and the quantity to order per item. The results show that using these recommendations, Optimas can save up to 50% of their total inventory cost while maintaining their customers’ required service level. 2021-06-16T19:07:44Z 2021-06-16T19:07:44Z 2021-06-16 Other https://hdl.handle.net/1721.1/130970 en_US CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ application/pdf |
| spellingShingle | Demand Planning Inventory Management Efendigi, Esat Cameron, Kristin Katharine Inventory Management for Slow Moving and High Volatility Items |
| title | Inventory Management for Slow Moving and High Volatility Items |
| title_full | Inventory Management for Slow Moving and High Volatility Items |
| title_fullStr | Inventory Management for Slow Moving and High Volatility Items |
| title_full_unstemmed | Inventory Management for Slow Moving and High Volatility Items |
| title_short | Inventory Management for Slow Moving and High Volatility Items |
| title_sort | inventory management for slow moving and high volatility items |
| topic | Demand Planning Inventory Management |
| url | https://hdl.handle.net/1721.1/130970 |
| work_keys_str_mv | AT efendigiesat inventorymanagementforslowmovingandhighvolatilityitems AT cameronkristinkatharine inventorymanagementforslowmovingandhighvolatilityitems |