Inventory Management System for Hidden Cost Savings Documentation
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Solution Overview
Problem
Current inventory management systems lack the ability to identify and document cost-saving opportunities, leading to unseen and unplanned costs such as excess inventory, lost productivity, and expediting costs, with suppliers often failing to provide satisfactory cost savings documentation to their customers.
Innovation Solution
A computer-based system and method that utilizes a business intelligence module, global data warehouse, and harvester program to quantify and document cost savings, providing actionable information on realized and potential savings through inventory management and supply chain optimization, including detailed reports and decision-making tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional inventory management systems are used, then basic inventory tracking is achieved, but cost saving opportunities remain hidden and undocumented
Solution Approach 1:
The patent embeds multiple analytical layers within the inventory management system - the harvester program collects data, the global data warehouse stores it, and the business intelligence module analyzes it to reveal hidden cost savings. Each layer nests within the system structure like dolls, with the innermost analysis layer revealing the previously hidden cost saving information without requiring a completely new external system.
Solution Approach 2:
The patent introduces intermediary components - the harvester program acts as a mediator between inventory operations and the data warehouse, while the business intelligence module serves as an intermediary between raw data and actionable cost saving insights. These intermediaries transform and structure information progressively, making hidden cost savings visible without direct complex connections between all system elements.
2Ease of operation
If suppliers provide detailed cost savings documentation, then customer satisfaction improves, but the time and resources required to generate documentation increase
Solution Approach 1:
The system performs preliminary data collection and validation through the harvester program, continuously gathering inventory and cost data before it is needed for analysis. The global data warehouse pre-stores structured data from multiple sources, so when cost savings analysis is required, the business intelligence module can immediately query and analyze pre-prepared data rather than collecting it in real-time, significantly reducing documentation preparation time.
Solution Approach 2:
The business intelligence module automatically analyzes inventory data and generates cost savings documentation without requiring manual intervention. The system self-services by autonomously querying the data warehouse, performing analytical calculations, and producing formatted reports that document cost savings, eliminating the need for manual data compilation and report generation.
3Measurement precision
If comprehensive data collection is implemented, then cost saving identification accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the data collection and processing function into distinct modular components: the harvester program handles data collection and validation, the global data warehouse manages data storage and organization, and the business intelligence module performs analysis. This segmentation allows comprehensive data collection across multiple sources while distributing processing complexity across separate, specialized modules rather than requiring one monolithic complex system.
Solution Approach 2:
The global data warehouse serves as an intermediary layer between raw data sources and the analysis module. It standardizes and structures data from various inventory and cost sources before analysis, transforming heterogeneous data into a uniform format that the business intelligence module can efficiently process, thereby reducing the complexity of direct data processing while maintaining comprehensive data collection.
Data Source
AI summary
A computer based system and method for inventory management, cost savings delivery and decision making is disclosed. A global data warehouse contains a cost savings delivery mechanism CSD-M that is configured to receive information from a business intelligence module to create cost savings documentation that identifies and quantifies cost savings that are realized by use of an inventory management system and potential cost saving opportunities that may be realized by use of supply chain and operational cost savings programs.