User Experience Management System for Granular Employee Satisfaction
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Solution Overview
Problem
Current customer satisfaction metrics, such as Net Promoter Score (NPS), fail to accurately assess employee satisfaction with internal company products and services, like email, video conferencing tools, and VPN services, which are crucial for employee productivity, and lack scalability to capture diverse employee populations across different locations and tasks.
Innovation Solution
A networked computing environment with a user experience management system that collects survey data from employees, integrates with help desk calls and system monitoring, and uses machine learning to identify and prioritize issues at a granular level, allowing for continuous feedback and resolution monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional customer satisfaction metrics like NPS are used to assess employee satisfaction, then the assessment method is simple and familiar, but the accuracy of assessing employee satisfaction with internal products and services deteriorates
Solution Approach 1:
The patent segments the assessment system into multiple specialized components: survey management system for collecting feedback, help desk system for tracking issues, system monitoring for technical metrics, and machine learning analysis for insights. Each component handles specific aspects of employee experience assessment, improving measurement precision while distributing complexity across modular systems rather than using a single monolithic approach.
2Reliability
If comprehensive survey data is collected from all employees across different locations and tasks, then the representativeness and completeness of feedback improves, but the scalability and ease of data collection deteriorates
Solution Approach 1:
The survey management system is designed as a universal platform that can deploy standardized surveys across diverse employee populations while adapting to different locations, roles, and product teams. The system collects both quantitative survey responses and qualitative feedback through multiple channels (email, mobile apps, web portals), enabling scalable data collection that maintains representativeness across the entire employee base regardless of organizational structure or geographic distribution.
3Measurement precision
If manual analysis of survey results is used to identify employee satisfaction issues, then the analysis process is simple to implement, but the ability to identify specific product or service problems at granular level deteriorates
Solution Approach 1:
The system implements automated feedback loops where machine learning algorithms continuously analyze survey responses, help desk tickets, and system monitoring data to identify patterns and root causes of employee dissatisfaction. The insights generated are fed back to product teams for targeted improvements, and the system continuously learns from new data to refine its problem identification accuracy, enabling granular issue detection through intelligent automation rather than manual analysis.
4Reliability
If multiple data sources (surveys, help desk calls, system monitoring) are integrated to comprehensively identify problems, then the completeness of problem identification improves, but the complexity of data integration and processing deteriorates
Solution Approach 1:
The patent merges multiple previously separate systems (survey management, help desk, system monitoring) into an integrated employee experience management platform. This unified system consolidates data collection, storage, and analysis functions across all data sources, enabling comprehensive problem identification through centralized processing while reducing the operational complexity of managing multiple disconnected systems. The integration allows cross-referencing between survey feedback, help desk tickets, and technical metrics to identify root causes more effectively.
Data Source
AI summary
A user experience management system obtains survey results providing insight on the user's experience with provided products and services. Periodically, the user experience management system uses these results in conjunction with the help desk data and the user experience management system monitoring data to identify the set of problems with specific products and services on a granular level. The product management system generates a resolution to address a problem definition generated by the user experience management system. The user experience management system monitors the resolution and updates the database with data pertaining to the resolution. Other embodiments are disclosed herein.