Decision Management System for Visualizing Interconnected Policy Effects
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Solution Overview
Problem
Current decision management technologies lack the intelligence to predict and notify human operators about the global effects of changes in local decision assets on other decision assets within or outside an organization, due to the complex web of associations among decision factors.
Innovation Solution
A computer-implemented decision management system that monitors changes in decision factors by determining the strength of relationships between nodes in a decision hierarchy, using a graphical interface to visually represent these relationships and alert users to potential changes, allowing for a better understanding of cause-and-effect relationships across different levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a policy change is made at one level in the decision hierarchy, then decisions at that level can be updated, but it becomes impossible to understand the downstream and upstream consequences across the complex web of associations
Solution Approach 1:
The patent segments the complex decision hierarchy into discrete decision assets (nodes) and their relationships (edges). Each decision asset is represented as an individual unit with defined attributes, allowing the system to break down the overwhelming complexity into manageable, analyzable components while preserving the overall structure and relationships.
Solution Approach 2:
The patent implements feedback mechanisms that automatically track and report the downstream and upstream consequences of policy changes. When a decision asset changes, the system propagates this information through the relationship network and generates notifications about affected assets, providing continuous feedback loops that maintain awareness of cause-and-effect relationships across the hierarchy.
2Reliability
If the complete web of associations among all decision factors is mapped, then comprehensive understanding of relationships is achieved, but the complexity becomes unmanageable for human operators
Solution Approach 1:
The patent replaces the mechanical cognitive burden of manually tracking complex relationships with an automated computational system. The computer-implemented decision management system performs the complex analysis, tracking, and relationship mapping automatically, freeing human operators from the impossible task of mentally managing the complete web of associations while maintaining complete and accurate relationship data.
3Productivity
If traditional management dashboards are used to track events, then timelines and deadlines are monitored, but the system lacks intelligence to predict or notify about global effects of local changes
Solution Approach 1:
The patent implements preliminary action by proactively predicting and notifying about global effects before they manifest as problems. The system uses the relationship network to anticipate downstream consequences of local changes and generates advance notifications, allowing operators to prepare for and mitigate potential issues before they occur, rather than merely reacting to events after they happen.
Data Source
AI summary
Computer-implemented decision management systems and methods are provided. The method comprises obtaining information associated with factors usable for making a decision from among a plurality of inter-related decisions represented by a plurality of corresponding nodes. The computing environment provides access to resources that store information about relationships among the plurality of nodes. A relationship may be presentable as an edge connecting at least two nodes from among the plurality of nodes. The strength of the relationship between the at least two nodes is measurable and definable based on associations between the inter-related decisions. A valued may be determined that provides a measure for the strength of the relationship between the at least two nodes based on the information associated with the factors and the information about the relationships among the plurality of nodes.