Supply Knowledge Portal Metric Dashboard
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Solution Overview
Problem
Traditional database models for tracking transactions in supply chains are inefficient for storing, updating, and accessing information, requiring massive databases and being cumbersome for generating reports from point-of-use devices in hospital settings.
Innovation Solution
A supply knowledge portal system that includes a database server with an analysis database generating pre-computed metric values, allowing quick access to supply chain information through a metric dashboard, facilitated by point-of-use devices that provide controlled access and transaction data to the server via a network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transaction-based storage is used to track supply chain transactions, then complete tracking information can be stored, but massive databases are required and access efficiency deteriorates
Solution Approach 1:
The database is segmented into multiple partitions, each storing a subset of transaction data. This segmentation allows parallel access to different data subsets, improving query performance while maintaining complete tracking information across all partitions.
Solution Approach 2:
Summary data and aggregated metrics are pre-computed and stored in the database before queries are executed. This preliminary action eliminates the need for complex real-time computations during data access, significantly improving retrieval speed while preserving complete transaction details.
2Loss of information
If traditional database models are used for supply chain data, then all transaction details can be stored, but storage requirements and system complexity increase
Solution Approach 1:
Different parts of the database system are optimized for different functions: raw transaction data is stored in a standardized format in one partition, while aggregated summary data is stored in another partition optimized for quick retrieval. This local optimization reduces overall system complexity while retaining all necessary information.
Solution Approach 2:
An intermediary processing layer is introduced between data storage and data retrieval operations. This intermediary pre-processes and organizes data into efficient query structures, reducing the complexity of direct database access while maintaining complete transaction information availability.
3Ease of operation
If bulk download of transaction information is implemented, then reports can be generated, but data access time and processing overhead increase
Solution Approach 1:
Summary statistics and aggregated metrics are pre-computed and stored alongside raw transaction data. When reports are generated, users can directly access these pre-computed values without requiring bulk download and real-time processing of all transaction records, dramatically reducing data access time while maintaining ease of report generation.
Data Source
AI summary
Systems and methods are provided for a supply knowledge portal. The supply knowledge portal provides a new metric dashboard that delivers real-time information on the status and health of the hospital supply chain. The new dashboard is driven by the transactional data generated from system point of use devices and allows end users to view data at various levels starting at the facility level and moving down to filter for specific areas, devices and, at the lowest level, items.