Interactive Rescheduling Interface for Multi-Metric Schedule Analysis
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Solution Overview
Problem
Existing data systems struggle to efficiently reschedule items due to disparate data stores and formats, leading to an unfeasible evaluation of rescheduling options and their effects on various metrics.
Innovation Solution
A data analysis system that receives time-sensitive and other data from a master data system, utilizing sophisticated data analysis and interactive graphical user interfaces to efficiently evaluate and implement rescheduling options, considering multiple metrics, and dynamically update user interfaces in response to user inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data from multiple disparate data stores and databases are combined to enable holistic evaluation of rescheduling options, then the completeness of data analysis is improved, but the system complexity and computational burden increase exponentially
Solution Approach 1:
The patent segments the complex rescheduling evaluation into distinct modules: a data collection module that gathers information from multiple disparate data stores, a metric evaluation module that assesses multiple metrics, and a rescheduling option generation module. This modular segmentation allows comprehensive data analysis while managing system complexity through organized, separable components.
Solution Approach 2:
The patent introduces an intermediary computing system that acts as a mediator between the disparate data stores and the rescheduling evaluation process. This intermediary system standardizes data formats, integrates information from multiple sources, and presents unified rescheduling options, thereby reducing the complexity burden on individual components while maintaining holistic data analysis.
2Measurement precision
If multiple metrics and variables are evaluated simultaneously to assess rescheduling options, then the accuracy of rescheduling decisions is improved, but the computational time and resources required increase
Solution Approach 1:
The patent performs preliminary actions by pre-defining multiple metrics and evaluation criteria before the actual rescheduling decision is needed. The system pre-processes data from various data stores and pre-evaluates potential rescheduling options against established metrics, so that when a rescheduling decision is required, the computationally intensive work has already been completed or can be quickly finalized.
Solution Approach 2:
The patent dynamically adjusts evaluation parameters and metric weights based on the specific rescheduling context and user preferences. By changing parameters such as which metrics are prioritized or how they are weighted, the system can focus computational resources on the most relevant evaluations, improving decision accuracy while reducing unnecessary computational overhead.
3Speed
If real-time data processing is implemented to provide up-to-date rescheduling information, then the responsiveness of the system is improved, but the energy consumption and processing load increase
Solution Approach 1:
The patent implements periodic action by processing data at strategically determined intervals rather than continuously. The system updates rescheduling evaluations periodically based on trigger events such as schedule changes, metric threshold violations, or user interactions. This periodic processing maintains system responsiveness to important changes while significantly reducing energy consumption compared to continuous real-time processing.
Data Source
AI summary
A data analysis system is disclosed that receives data from a master data system to enable useful and efficient rescheduling of items, taking into account effects of various rescheduling options on various metrics related to the items and/or the scheduling. The data analysis system includes sophisticated data analysis and interactive graphical user interface functionality to enable efficient, multi-variable evaluation of various rescheduling options. The interactive graphical user interface includes interactive functionality for suggesting rescheduling options in view of the effects of those changes on various metrics, evaluating various rescheduling options in view of effects on the various metrics, adjusting instances of metrics related to items/timelines in view of scheduling changes, and the like. Once a set of schedule modifications are determined by the data analysis system, the data analysis system can push the schedule modifications back to the master data system for implementation.


