Meeting Composition Scoring for Redundant Attendee Detection
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Solution Overview
Problem
Existing automated scheduling systems are ineffective in recommending optimal meeting locations and attendee mixes, leading to inefficient meetings due to lack of real-time information and inability to dynamically adjust to user attributes and requirements.
Innovation Solution
A system that retrieves user IDs and characteristics, applies scoring rules to determine meeting redundancy, and generates insights to optimize meeting composition by identifying and removing redundant attendees, thus improving meeting efficiency and productivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If automated scheduling systems send meeting invitations to all potential attendees without filtering, then no information is lost about potential participants, but meeting efficiency deteriorates due to redundant attendance
Solution Approach 1:
The system performs preliminary analysis of user characteristics and meeting requirements before sending invitations. It calculates a meeting composition score for each potential attendee based on their attributes (department, role, location, etc.) and the meeting's stated objectives, pre-filtering the attendee list to exclude unlikely candidates before the meeting organizer receives the invitation list.
Solution Approach 2:
The patent replaces the mechanical/manual process of organizers manually selecting attendees with an automated intelligent system. The system uses machine learning models and algorithms to automatically analyze user profiles, meeting objectives, and organizational data to determine optimal attendance, substituting human judgment with data-driven automated decision-making.
2Productivity
If the system analyzes user characteristics and scores meeting composition to identify redundant attendees, then meeting efficiency improves by reducing redundant attendance, but system complexity increases
Solution Approach 1:
The system segments the complex task of attendee selection into distinct analytical components: it separately evaluates user characteristics (department, role, location), meeting objectives, and organizational hierarchy. Each segment is scored independently using specific algorithms, and the results are aggregated to produce an overall meeting composition score, making the complex decision process modular and manageable.
Solution Approach 2:
The patent introduces an intermediary intelligent system that acts as a mediator between the meeting organizer's requirements and the potential attendees. This intermediary system processes the complex analysis of user characteristics and meeting objectives, then presents simplified recommendations to the organizer, shielding them from the underlying system complexity while delivering value.
3Measurement precision
If the system provides detailed analytics and recommendations about meeting composition, then decision quality improves, but information processing requirements increase
Solution Approach 1:
The system applies local quality by providing differentiated levels of analytical detail to different users and contexts. For straightforward meeting scenarios, it provides concise recommendations. For complex scenarios involving multiple departments and roles, it provides more detailed breakdowns of the scoring criteria and rationale, ensuring that information processing volume matches the actual decision complexity required.
Data Source
AI summary
This disclosure describes, according to some implementations, a method for scoring electronic meeting requests for attendee redundancy. In an example method, the method includes retrieving, using one or more processors, user IDs of meeting attendees; retrieving, using the one or more processors, one or more characteristics associated with the user IDs; retrieving, using the one or more processors, a rule having one or more parameters for scoring meeting composition; comparing, using the one or more processors, the one or more characteristics associated with the user IDs based on the one or more parameters of the rule; and generating, using the one or more processors, a meeting score based on the comparison.