Causal Analysis System for Organizational Outcome Prediction
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Solution Overview
Problem
Conventional methods for analyzing organizational operations and achieving outcomes fail to effectively visualize causality connections, predict future influences, and account for multiple threat and response scenarios, leading to inefficiencies and impossibilities in decision-making, especially when outcomes span beyond a single user's scope or involve unrepresented factors.
Innovation Solution
A method and system for causal analysis using an operating model that defines outcomes, connects it to data for predictive calculations, and provides interactive visualization, allowing for simulation of interventions and automated analysis to optimize outcomes, while accounting for cyber situational awareness and time-based influences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional methods (strategy mapping, goal trees, statistical models) are used to represent the organization, then the representation can be delivered at a point in time, but the system cannot provide live support and requires manual adjustment of variables
Solution Approach 1:
The patent replaces manual mechanical adjustment of variables with automated computational algorithms that dynamically calculate and update organizational representations in real-time based on input data, eliminating the need for manual variable adjustment while maintaining live system support
Solution Approach 2:
The system automatically maintains and updates its own organizational representation by processing incoming data and recalculating relationships without requiring manual intervention, allowing the representation to serve itself rather than requiring continuous human adjustment
2Productivity
If data-led techniques are used to aggregate results upwardly into outcomes, then analysis can be performed on available data, but other factors influencing outcomes that are not represented in the data are not taken into account
Solution Approach 1:
The patent creates a unified organizational representation that serves multiple functions simultaneously: it processes available data, incorporates expert knowledge about unrepresented factors, and provides both analysis and forecasting capabilities, eliminating the need to choose between data-driven and knowledge-driven approaches
Solution Approach 2:
The patent introduces an intermediary layer in the form of a comprehensive organizational representation that mediates between raw data and final outcome analysis, translating both data-driven insights and expert knowledge into a unified framework that accounts for all relevant factors
3Loss of information
If conventional diagram or chart approaches are used to show influence of assets, then the influence can be visualized, but the user cannot visualize projected consequential influences over time or simulate multiple scenarios
Solution Approach 1:
The patent transforms static diagrams into dynamic, interactive visualizations that can simulate multiple scenarios and project consequential influences over time by allowing users to modify input parameters and observe real-time updates to the organizational representation and its outcomes
Solution Approach 2:
The system performs preliminary calculations and projections by pre-computing the effects of potential actions on organizational outcomes, allowing users to visualize projected consequences before implementing actual changes to the organization
Data Source
AI summary
The present invention relates to the creation of a method and system for the analysis of the operations of an organisation with regard to their achievement of organisation outcomes, by the generation of causal modelling systems and the implementation of the same in conjunction with a landscape model of the organisation. A visual generation system to allow user interaction with a display screen is also provided to allow the navigation of the properties of the organisation and outcomes within the organisation to be selected and analysed.