Inventory Engine Optimizing Micro-warehouse Selection
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Solution Overview
Problem
Electronic marketplace providers face challenges in selecting an optimal inventory for micro-warehouses with limited capacity, as national demand forecasts fail to accurately predict consumer demand in smaller geographical areas, leading to suboptimal inventory selection, decreased revenue, and delayed delivery times.
Innovation Solution
An inventory engine is developed to determine an optimal set of items for micro-warehouses by generating regional demand forecasts from national data, considering factors like substitution, complementary, and competitor-offered items, and adjusting inventory based on real-time demand and storage constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If national demand forecasts are used to stock warehouses, then inventory selection is simplified, but accuracy of demand prediction for smaller geographical areas deteriorates
Solution Approach 1:
The patent segments the national demand forecast into regional components by geographically dividing the service area into multiple regions and generating separate demand forecasts for each region. This allows the system to maintain simplicity at the national level while achieving precision at the regional level, directly resolving the contradiction between simplified inventory selection and accurate local demand prediction.
2Quantity of substance
If inventory is optimized for limited storage capacity, then storage efficiency improves, but delivery time may be delayed if items are unavailable
Solution Approach 1:
The patent applies preliminary action by pre-positioning items in micro-warehouses based on predicted regional demand before actual customer orders are placed. The system forecasts demand, identifies items likely to be ordered, and proactively stocks them in advance in appropriate micro-warehouses, ensuring items are available for immediate delivery when ordered while optimizing storage capacity utilization.
3Reliability
If more items are stocked in micro-warehouses, then customer demand fulfillment improves, but storage costs and wasteful storage increase
Solution Approach 1:
The patent changes the parameter of inventory allocation from a uniform national approach to a dynamic regional approach. By adjusting inventory levels in each micro-warehouse based on specific regional demand parameters, the system optimizes the balance between demand fulfillment and storage efficiency, ensuring items are stocked where and when needed without excessive storage anywhere.
Data Source
AI summary
Techniques are provided herein for utilizing an inventory engine to optimize the selection of a set of items to be stored as inventory at a storage location. A candidate set of items may be identified based at least in part on a selection model. In accordance with at least one embodiment, the selection model may be based at least in part on a capacity of the storage location and a threshold time duration by which purchased items of the set of items are to be transported from the storage location to a purchaser. A plurality of probability values corresponding to the candidate set of items may be determined. An optimal set of items may be determined based at least in part on the candidate set of items and the plurality of probability values.