Procurement-Integrated Allocation Table Generation
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Solution Overview
Problem
Current business models face challenges in synchronizing allocation systems with procurement systems, leading to inefficiencies in merchandise allocation and management, particularly in complex retail environments with vast product variations and multiple store locations.
Innovation Solution
The development of systems and methods that generate allocation tables directly from procurement systems, using both fixed and variable quantity allocation strategies based on historical data, to optimize inventory distribution across stores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If allocation systems operate independently from procurement systems, then operational flexibility is maintained, but integration efficiency and synchronization capability deteriorate
Solution Approach 1:
The patent merges the allocation system and procurement system into a unified integrated system where allocation tables are generated directly from procurement data. This combination eliminates the need for independent operation while maintaining synchronization capability, resolving the contradiction by achieving both integration efficiency and operational flexibility through a single cohesive system architecture.
2Ease of operation
If fixed quantity allocation is used for all stores, then allocation simplicity is maintained, but inventory optimization and profitability deteriorate
Solution Approach 1:
The patent implements local quality by allowing different allocation strategies for different stores based on their specific characteristics. While the system maintains overall simplicity through automated processing, it applies variable quantity allocation to specific stores where historical data indicates optimization benefits, thus achieving both ease of operation and inventory optimization through differentiated local approaches.
3Reliability
If variable quantity allocation based on historical data is implemented for each store, then inventory optimization improves, but system complexity and data processing requirements deteriorate
Solution Approach 1:
The patent applies self-service by enabling the system to automatically generate allocation tables using historical data without requiring manual intervention for each store. The system autonomously processes historical sales data, calculates optimal quantities, and generates allocation recommendations, thereby achieving inventory optimization while minimizing the perceived complexity for users through automated self-service functionality.
4Measurement precision
If allocation tables are generated manually, then allocation accuracy can be controlled, but time consumption and productivity deteriorate
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors allocation performance, compares actual sales with allocated quantities, and uses this feedback to refine future allocation decisions. This automated feedback loop maintains allocation accuracy by learning from historical data while dramatically reducing time consumption through automated processing, eliminating the need for manual table generation while preserving precision through data-driven adjustments.
Data Source
AI summary
A method, apparatus and program product are provided for generating an allocation table in a computerized procurement system. The method comprises receiving first data from a purchase order regarding a plurality of articles to be allocated, and receiving second data from an assortment regarding the plurality of articles and a plurality of stores identified for receiving the articles at specified times. The method further comprises determining a fixed quantity of each article to be allocated to each store based on at least one of the first and second data, wherein the fixed quantity of each article is the same for all stores. The method also comprises determining a variable quantity of each article to be allocated to each store, wherein the variable quantity of each article is individually set for each store, and wherein the variable quantity of each article is determined based on analysis of historical data.