Scheduling System Disruption Factor Calculation
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Solution Overview
Problem
Existing electronic calendaring systems often fail to consider the preferences and convenience of all invitees, particularly those in different time zones, when scheduling collaborative events, leading to potentially disruptive or inconvenient meeting times and locations.
Innovation Solution
A computer program product and method that associate a disruption factor with each invitee based on event parameters and invitee attributes, such as time zone location, to recommend and enforce alternative times and locations that minimize disruption, using weighting factors to account for invitee characteristics and attendance likelihood.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the scheduler schedules the collaborative event according to the scheduler's preferences and convenience, then the scheduling process is simple and quick, but the preferences and convenience of other parties may not be fully considered
Solution Approach 1:
The system automatically calculates disruption factors and generates scheduling recommendations without requiring manual input from the scheduler about each invitee's preferences. The scheduler simply provides basic event parameters, and the system self-services by computing the equitable schedule based on stored invitee attributes and disruption factor formulas.
Solution Approach 2:
The system provides feedback to the scheduler in the form of disruption factor calculations and recommended schedules. This feedback loop allows the scheduler to see the impact of different scheduling options on invitees and adjust the schedule accordingly, balancing efficiency with equitability.
2Ease of operation
If the scheduler considers the preferences of all parties in different time zones, then the scheduling becomes more equitable, but the scheduling process becomes more complex and time-consuming
Solution Approach 1:
The system automatically performs the complex calculations of disruption factors by retrieving invitee attributes (time zones, working hours, preferences) from storage and applying predefined formulas. This eliminates the need for the scheduler to manually consider each factor, maintaining equitability while reducing complexity.
Solution Approach 2:
Invitee attributes such as time zones, working hours, and scheduling preferences are pre-stored in the system database. When scheduling is needed, the system already has this information ready, eliminating the need for real-time data collection and reducing the complexity of the scheduling process.
3Object-affected harmful factors
If alternative times and locations are recommended based on disruption factors, then the meeting becomes less disruptive to invitees, but additional computational processing is required
Solution Approach 1:
The system calculates disruption factors for a limited set of candidate times and locations rather than evaluating all possible options. By focusing on a reasonable subset of alternatives, the system reduces computational power requirements while still identifying sufficiently good scheduling options that minimize disruption to invitees.
Data Source
AI summary
An event scheduling request is received, and a disruption factor is associated with each of a plurality of invitees. The disruption factor is based upon, at least in part, an event parameter and at least one invitee attribute. An event is scheduled based upon, at least in part, the disruption factors associated with each of the plurality of invitees.