AI-Powered User Interface for Strategic Target Prioritization
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Solution Overview
Problem
Existing software user interfaces for business data analysis overwhelm users with too many options and variables, leading to complex and disorganized interfaces that lack an efficient mechanism for intelligent analysis.
Innovation Solution
A system utilizing artificial intelligence algorithms to identify and prioritize targets for emphasis, presenting a user interface that allows manual selection based on statistical and AI analysis, focusing on key performance indicators (KPIs) to improve strategy health scores by selectively emphasizing specific targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing software user interfaces present all available KPIs and data options to users, then comprehensive information is provided, but the interface becomes overwhelming and confusing
Solution Approach 1:
The system extracts and prioritizes only the most relevant KPIs and data points from the complete dataset, presenting a curated subset to users based on AI analysis of current goals and context, thereby reducing information overload while maintaining comprehensiveness
Solution Approach 2:
The interface dynamically adjusts the presentation of data based on local context and user needs, emphasizing different KPIs and details in different regions of the interface according to their relevance to current business objectives and user roles
2Quantity of substance
If existing software user interfaces display comprehensive KPIs, then all important information is available, but the interface becomes complex and disorganized
Solution Approach 1:
The system segments the comprehensive set of KPIs into organized groups and categories based on their relationships and relevance, presenting them in a structured hierarchy that reduces complexity while maintaining completeness
Solution Approach 2:
The interface dynamically reorganizes and adapts the presentation of KPIs based on current context, user interactions, and AI analysis, transforming the static complex layout into a dynamic organized structure that responds to user needs
3Quantity of substance
If existing software user interfaces present extensive data options, then complete business analysis is possible, but intelligent analysis capability is lacking
Solution Approach 1:
The system introduces an AI intermediary layer between the raw data and the user interface, which automatically analyzes the extensive data, identifies relevant patterns and insights, and presents only the most valuable information to users, thereby enabling intelligent analysis without overwhelming the interface
Data Source
AI summary
The present disclosure uses statistical analysis and an artificial intelligence (AI) algorithm to identify a plurality of targets for emphasis. An emphasis is a real-world activity that is designed to lead to a desired behavior by a target. The targets are assigned to strategies based on attributes associated with the targets. Strategies define different portions of a life cycle associated with the targets. Each strategy is rated according to its health, which is defined according to primary indicators for that strategy. Emphasis is placed on targets in an attempt to improve the primary indicators for a strategy. A user interface allows for selection of targets in a manner that improves the health of weak strategies and indicators as predicted by the AI algorithm instead of focusing on a single overall metric for all targets being analyzed.