Employee Sentiment Survey Feedback Loop for Verified Emotion Capture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing employee satisfaction surveys lack the ability to accurately capture and verify emotional sentiment, leading to incomplete understanding of employee happiness and hinder effective organizational interventions.
Innovation Solution
A computing system that collects, verifies, and reports emotional sentiment data by presenting digital surveys, inferring emotional states from responses, allowing participants to confirm or revise these inferences, and aggregating verified data for comprehensive reporting and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional employee satisfaction surveys are used to gather feedback, then employees can share their thoughts and concerns, but the emotional sentiment captured is incomplete and inaccurate
Solution Approach 1:
The patent replaces traditional mechanical survey response collection with AI-powered natural language processing and sentiment analysis systems. The system automatically analyzes written comments and responses to infer emotional states, then presents these inferences to employees for verification. This substitution enables precise emotional sentiment measurement while preserving complete emotional context information through the verification process.
Solution Approach 2:
The patent implements a feedback loop where the system analyzes survey responses to generate emotional sentiment inferences, presents these inferences to employees for confirmation or correction, and uses the verified feedback to improve future survey analysis. This iterative feedback process continuously refines measurement accuracy while ensuring complete capture of employee emotional states.
2Reliability
If surveys ask employees directly about their happiness, then responses are straightforward, but employees may not accurately reflect their true emotional states
Solution Approach 1:
The patent substitutes direct self-reporting with AI-based natural language analysis of employee responses. The system analyzes the linguistic patterns, tone, and context of written comments to infer emotional states, then presents these inferences to employees for verification. This approach captures subtle emotional nuances that employees might not directly articulate while maintaining reliability through the verification process.
Solution Approach 2:
The patent introduces an intermediary layer between the survey questions and the emotional sentiment measurement. The AI sentiment analysis system acts as this intermediary, translating raw survey responses into inferred emotional states, which are then verified with employees. This intermediary process preserves subtle emotional nuances while improving the accuracy of sentiment measurement.
3Loss of information
If the survey system collects detailed emotional data, then insights into employee happiness improve, but the complexity of data processing increases
Solution Approach 1:
The patent uses a feedback mechanism where the system presents emotional sentiment inferences to employees for verification. This feedback loop allows the system to process detailed emotional data in a structured manner, verifying each inference individually. The feedback process simplifies the overall data processing complexity by providing a clear, step-by-step approach to handling detailed emotional context information.
Solution Approach 2:
The patent segments the data processing into distinct manageable steps: collecting survey responses, analyzing them to generate emotional inferences, presenting inferences for verification, and finalizing the verified sentiment data. This segmentation reduces the complexity of processing detailed emotional context by breaking down the overall process into simpler, sequential operations.
4Measurement precision
If the system verifies emotional sentiment with employees, then measurement accuracy improves, but survey completion time increases
Solution Approach 1:
The patent implements self-service by having employees verify or correct their own emotional sentiment inferences directly in the survey interface. Employees review the AI-generated inferences and confirm or adjust them as needed, taking control of their own data input. This self-service approach improves measurement precision through personal verification while minimizing time loss by allowing employees to quickly confirm or correct inferences at their own pace.
Solution Approach 2:
The patent applies partial action by providing employees with pre-analyzed emotional inferences that require only minimal verification or correction rather than requiring complete re-response. The system performs the bulk of the analysis work upfront, and employees only need to verify or make minor adjustments, reducing the overall time required while maintaining high measurement precision.
Data Source
AI summary
The present disclosure is directed to satisfaction surveys for measuring the presence of positive emotions and experiences, the absence of negative emotions and experiences, and identifies when users are getting what they need or want. More significantly, the survey gathers real-time data based on participant responses. Then, and before the survey ends, the system presents each participant with a happiness feeling that represents how it appears they feel (based on their unique responses to the Happiness Survey, for example). Survey participants are then asked if that is how they often feel, and if not, they may simply select a happiness feeling that matches how they actually feel. The result is a verified feeling.