Two-Layer Causal Model for Enterprise Scenario Simulation
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Solution Overview
Problem
Current enterprise and business model visualization techniques fail to represent causal relationships between elements and sub-elements, and do not allow for the analysis or simulation of the influence of business factors on causally linked elements, leading to ineffective management and increased complexity in understanding organizational changes.
Innovation Solution
A method and system with a two-layer model, where the first layer represents the 'real world' organization with elements and sub-elements connected by links, and the second layer shows causal influences and factors affecting these elements, allowing users to quantify and visualize the degree of influence using data from databases, enabling simulation of outcomes and reducing the need for skilled analysts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If diagrammatic visualization of interdependence is used, then the relationship between elements can be shown, but the causal effect and degree of influence cannot be represented
Solution Approach 1:
The model is divided into two distinct layers: a first model layer for diagrammatic visualization of interdependence relationships, and a second model layer for representing causal influences and factors. This segmentation allows each layer to serve its specific function without compromising the other, resolving the contradiction between visualizing relationships and representing causal effects.
Solution Approach 2:
The patent transitions from a single-layer diagrammatic model to a two-layer model, adding another dimension of analysis. The second layer builds upon the first layer by incorporating causal influence representations, enabling the model to simultaneously show both interdependence relationships and causal effects without increasing complexity.
2Adaptability or versatility
If current visualization techniques are used, then organizational structure can be displayed, but the degree of influence of business factors cannot be analyzed or simulated
Solution Approach 1:
The second model layer enables dynamic scenario simulation by allowing users to modify factor values and observe the propagation of changes through causal links. This dynamic capability provides adaptability for exploring different scenarios while maintaining accurate representation of influence degrees through quantitative data.
Solution Approach 2:
The model incorporates feedback mechanisms where changes in factor values in the second layer propagate back through causal links to affect element attributes, and this information can be used to adjust the model further. This feedback loop enables both scenario simulation and accurate influence analysis.
3Productivity
If organizational complexity increases, then more detailed analysis is possible, but the rate of change cannot keep up with the pace of change
Solution Approach 1:
By segmenting the model into two layers with distinct functions, the system can process organizational complexity more efficiently. The first layer handles high-level interdependence relationships while the second layer manages causal influences, allowing faster analysis without sacrificing detail.
Solution Approach 2:
The model allows users to selectively explore different levels of detail by switching between layers or focusing on specific causal chains. This partial action approach enables rapid analysis of critical areas without requiring complete processing of the entire complex organizational structure.
Data Source
AI summary
This invention relates to a method for creating and using a dynamically-generated model with a visual display of the model. The model has first and second layers relevant to the organization for which the model is generated. Different projects within the organization can be represented and explored by the user, each project having a plurality of features represented by elements and one or more sub-elements, with the first layer including one or more elements and one or more sub-elements connected by one or more links indicating a relationship between two or more of the elements and/or sub-elements, and at least one element and/or sub-element includes one or more attributes associated therewith and the second layer includes the one or more elements and/or sub-elements connected by the one or more links and further includes links to one or more factors or components that influence one or more linked elements, sub-elements and/or attributes.