Inventory Target Determination Using Segmented Demand and Variability Stocks
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Solution Overview
Problem
Existing supply chain analysis techniques fail to accurately predict the amount of inventory needed at nodes, leading to inefficiencies and inaccuracies in inventory management.
Innovation Solution
Calculating a demand stock to cover mean demand over lead time and a demand variability stock to cover demand variability over lead time, with an inventory target determined based on these calculations, allowing for adjustments in supply lead time and demand variability to optimize inventory levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If known techniques are used to determine inventory amount, then the process is simple, but the prediction accuracy of inventory needed at nodes is insufficient
Solution Approach 1:
The patent segments the inventory determination process into distinct components: demand stock calculation and demand variability stock calculation. This segmentation allows each component to be optimized independently, improving overall prediction accuracy while maintaining manageable complexity through structured decomposition of the problem.
Solution Approach 2:
The patent introduces specific parameters (demand stock, demand variability stock, service level) to transform the inventory determination process. By changing from a single aggregate inventory figure to multiple differentiated parameters, the system achieves higher prediction accuracy while the standardized parameter framework prevents complexity from becoming unmanageable.
2Measurement precision
If inventory target is optimized for accuracy, then prediction precision improves, but calculation complexity increases
Solution Approach 1:
The calculation process is divided into two separate but related calculations: demand stock (mean demand × lead time) and demand variability stock (service level × demand variability × lead time). This segmentation improves accuracy by addressing different aspects of inventory needs separately, while keeping each calculation relatively simple and independent.
Solution Approach 2:
The patent incorporates service level as a feedback parameter that adjusts the demand variability stock calculation. This feedback mechanism allows the system to adapt to varying accuracy requirements without fundamentally changing the calculation structure, maintaining reasonable complexity while achieving high precision through parameter adjustment.
Data Source
AI summary
Determining an inventory target for a node of a supply chain includes calculating a demand stock for satisfying a demand over supply lead time at the node of the supply chain, and calculating a demand variability stock for satisfying a demand variability of the demand over supply lead time at the node. A demand bias of the demand at the node is established. An inventory target for the node is determined based on the demand stock and the demand variability stock in accordance with the demand bias.