Inter-store Inventory Transfer Optimization
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Solution Overview
Problem
Retailers face challenges in making real-time inter-store inventory transfer decisions to satisfy in-store customer demands, as existing methods lack the ability to quickly respond to out-of-stock situations, leading to potential losses or markdowns.
Innovation Solution
A computer-implemented method and system that uses a two-phase optimization approach, involving an inventory pool generation engine to select stores with minimal cost-to-serve for a demand zone and an alternate store selection engine to determine a suitable store for order fulfillment, enabling real-time inter-store inventory transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time inter-store inventory transfer decisions are implemented, then customer service and responsiveness are improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the inventory transfer decision-making process into two distinct phases: (1) pre-computation phase where the system defines a subset of stores and pre-calculates optimal transfer options, and (2) real-time execution phase where pre-determined rules quickly match customer orders with available inventory. This segmentation reduces real-time computational complexity while maintaining service reliability.
Solution Approach 2:
The system performs preliminary actions by pre-defining subsets of stores capable of fulfilling inter-store transfers and pre-establishing transfer rules before customer orders arrive. This allows the system to have inventory transfer decisions ready in advance, enabling rapid response to customer demands without complex real-time calculations.
2Productivity
If inventory transfer between stores is expedited, then loss of sales is reduced, but operational costs and logistics complexity increase
Solution Approach 1:
The patent applies local quality by defining specific subsets of stores with particular capabilities for inter-store transfers based on their location, inventory levels, and logistics capacity. Instead of treating all stores uniformly, the system identifies and utilizes only those stores that can efficiently fulfill transfer requests, optimizing both speed and cost.
Solution Approach 2:
The system dynamically changes parameters such as the composition of store subsets and transfer priorities based on current inventory levels, demand patterns, and operational constraints. This allows the system to adapt transfer decisions to minimize costs while maintaining rapid fulfillment capability.
Data Source
AI summary
Examples of techniques for generating an inter-store inventory transfer are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include defining a subset of stores of a plurality of stores to fulfill inter-store inventory transfer request for a product category of a plurality of product categories. The method may further include, responsive to determining that an order for a product of the product category cannot be fulfilled by one of the stores of the subset of stores of the plurality of stores, determining, by a processing device, an alternate store of the subset of stores to fulfill the order.