Adaptive SKU Determination Server with Trend Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In managing a large number of stores, headquarters face challenges in determining an appropriate number of SKUs (Stock Keeping Units) due to difficulties in assessing individual store conditions, leading to gaps between recommended and actual SKUs, and lack of feedback on current SKUs, making it hard to optimize inventory management.
Innovation Solution
A server system that calculates and transmits recommended SKUs based on past recommendations, with continuous adjustments based on trends in adopted SKUs from stores, allowing for dynamic updates and alignment with demand variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If headquarters determines the number of SKUs uniformly based on store scale, then the determination process is simple and efficient, but the accuracy of SKU recommendations decreases due to inability to account for individual store conditions
Solution Approach 1:
The patent implements a feedback mechanism where store terminals transmit adopted SKU numbers back to the headquarters server. The server accumulates this feedback data over time and uses it to dynamically adjust future SKU recommendations, transforming a static uniform determination into an adaptive system that improves accuracy while maintaining operational simplicity.
Solution Approach 2:
The system transitions from a static uniform SKU determination approach to a dynamic adaptive approach. The recommended SKU numbers are no longer fixed based solely on store scale, but are continuously adjusted based on accumulated feedback data and identified trends, allowing the system to adapt to changing store conditions while maintaining operational efficiency.
2Measurement precision
If headquarters attempts to determine SKUs based on detailed individual store conditions, then the accuracy of SKU recommendations improves, but the complexity of the determination process increases significantly
Solution Approach 1:
The store terminals autonomously determine their own adopted SKU numbers based on the recommended numbers received from headquarters and their local conditions. This self-service approach eliminates the need for headquarters to manually assess detailed store conditions, reducing system complexity while maintaining recommendation accuracy through automated local decision-making.
Solution Approach 2:
Headquarters pre-calculates recommended SKU numbers based on store scale and transmits them to store terminals in advance. The stores then use these pre-prepared recommendations as a baseline, adjusting only when necessary based on their specific conditions. This preliminary action simplifies the overall process by providing a ready-made starting point rather than requiring complex real-time determination.
3Adaptability or versatility
If the recommended number of SKUs is inappropriate, then stores must frequently correct the SKU numbers, but there is no feedback mechanism to inform headquarters of the current SKU status
Solution Approach 1:
The patent establishes a feedback loop where store terminals automatically transmit their adopted SKU numbers back to the headquarters server. This feedback mechanism ensures headquarters maintains current knowledge of store SKU status without requiring additional communication overhead, enabling continuous improvement of recommendation accuracy while preserving store flexibility to adjust SKUs as needed.
Data Source
AI summary
A recommended SKU number calculation unit 81 calculates a recommended number of SKUs on the basis of a number of SKUs recommended in the past. A recommended SKU number transmission unit 82 transmits the calculated recommended number of SKUs to a store terminal. In addition, in the case where an adopted number of SKUs sent back from a store in response to the transmitted recommended number of SKUs changes continuously and in a consistent trend, the recommended SKU number calculation unit 81 changes the recommended number of SKUs for the store, in accordance with the trend.