Relationship Index Calculation for Team Dynamics
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Solution Overview
Problem
Existing technologies for evaluating and improving interpersonal relationships within teams focus on superficial communication aspects, neglecting underlying relationships and often rely on subjective and burdensome questionnaires, leading to superficial improvements.
Innovation Solution
An information processing system that acquires user meeting and work information, calculates a relationship index based on both, and generates presentation information to assist in improving interpersonal relationships, using machine learning to predict and provide actionable insights without questionnaires.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If subjective questionnaires are used to evaluate interpersonal relationships, then the evaluation can be performed, but the burden on users increases and the results become subjective
Solution Approach 1:
The system automatically collects meeting information, work information, and communication data without requiring user participation in questionnaires. The evaluation is performed self-service style by the system itself, eliminating user burden while maintaining objective measurement through automated data analysis
Solution Approach 2:
The patent replaces the mechanical system of manual questionnaire completion with an automated information processing system that objectively evaluates relationships by analyzing meeting transcripts, work logs, and communication patterns, thereby eliminating subjective user input while maintaining measurement capability
2Measurement precision
If only superficial communication aspects are evaluated, then the evaluation process is simple, but the improvement achieved is superficial and does not address underlying relationship issues
Solution Approach 1:
The system segments relationship evaluation into multiple dimensions including communication patterns, work collaboration, meeting interactions, and underlying relationship dynamics. By dividing the evaluation into distinct analytical components, the system achieves deep comprehensive assessment while managing complexity through modular processing of different information types
Solution Approach 2:
The patent adds new dimensions to relationship evaluation by incorporating work information, meeting participation data, and communication patterns beyond superficial communication aspects. This multi-dimensional approach enables deep evaluation of underlying relationships while the automated system manages the complexity of analyzing multiple data dimensions simultaneously
3Productivity
If frequent evaluations are conducted to track relationship improvements, then timely insights are provided, but subjective questionnaires become burdensome and reduce compliance
Solution Approach 1:
The system continuously and automatically evaluates interpersonal relationships by continuously collecting and analyzing meeting information, work logs, and communication data without interruption. This continuous automated evaluation provides timely insights while maintaining high compliance because users are not repeatedly asked to complete questionnaires
Solution Approach 2:
The automated system performs continuous evaluation self-service style without requiring repeated user participation. The system independently collects data, processes information, and generates relationship assessments, enabling frequent evaluations while maintaining user compliance by eliminating the burden of repeated questionnaire completion
Data Source
AI summary
An information processing system includes: circuitry that acquires, from a terminal device used by each of a plurality of users, user meeting information indicating a state of a corresponding one of the plurality of users in a meeting in which the plurality of users participate; acquire work information related to a history of work-related activities of the plurality of users; calculate a relationship index indicating a relationship between the plurality of users based on the acquired user meeting information and the acquired work information, and store the relationship index in a memory; and generate, based on the relationship index that is stored, presentation information for presenting the relationship index to each of the plurality of users, and cause the terminal device to present the presentation information.