Chat Conversation Analysis for Work Engagement Estimation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for evaluating job seeker aptitude and managing organizational dynamics, such as talent identification and project management, face challenges in reducing the burden on individuals and accurately capturing subtle changes in work engagement and organizational dynamics.
Innovation Solution
An ability evaluating apparatus that uses conversation data from a chat system to calculate the number of mentions and proportions among teams, estimating work engagement by analyzing relationships and indicator values through a trained model, thereby reducing individual burden and enhancing the understanding of quick changes in work-related states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional aptitude tests are used to evaluate job seekers, then evaluation accuracy is improved, but the burden on the target person increases
Solution Approach 1:
The system uses the target person's own chat conversation data to automatically evaluate their work engagement and ability characteristics. The data acquisition unit collects conversation data from chat systems, and the evaluation unit processes this data to generate evaluations without requiring the target person to manually complete questionnaires or tests, thus reducing their burden while maintaining evaluation accuracy
Solution Approach 2:
The patent replaces traditional mechanical evaluation methods (manual questionnaires, standardized tests) with an automated information processing system that uses natural language processing to analyze chat conversation data. This substitution eliminates the need for direct human participation in the evaluation process while maintaining or improving evaluation quality
2Device complexity
If organizational distance-based management is used, then management simplicity is improved, but the ability to detect subtle changes in managed persons deteriorates
Solution Approach 1:
The system transitions from static organizational distance metrics to dynamic analysis of conversation data patterns. The evaluation unit continuously monitors conversation data to detect changes in work engagement levels, communication patterns, and interaction frequencies, enabling real-time detection of subtle changes in managed persons' states
Solution Approach 2:
The patent changes the evaluation parameters from fixed organizational distance values to dynamic conversation data characteristics such as mention frequency, conversation timing, and interaction patterns. This parameter transformation enables the system to detect subtle changes in work engagement and organizational dynamics that static distance metrics cannot capture
Data Source
AI summary
The present invention includes: a first data acquirer configured to, based on conversation data in a chat system, acquire a number of mentions provided by an evaluation target member of one team to each team within a first period; a first calculator configured to, based on the number of mentions provided by the evaluation target member to each team calculate a first proportion that is a proportion of the number of mentions provided by the evaluation target member to each team; and an estimator configured to, based on a relationship between a second proportion and a second indicator value, estimate a first indicator value corresponding to the first proportion, the second proportion being a proportion of a number of mentions provided by one member among a plurality of members of the organization to each team within a second period previous to the first period, the second indicator value being indicative of work engagement of the one member, the first indicator value being indicative of work engagement of the evaluation target member.