Workflow Relationship Management via Distributed Scanning
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Solution Overview
Problem
Conventional productivity systems require users to store all data in a central electronic repository, leading to high costs and inefficiencies, and burden users with manually identifying relationships between data components, creating a negative user experience.
Innovation Solution
A workflow management system that periodically scans multiple electronic data repositories to generate unique identifiers for files, builds an artificial intelligence model to identify related files based on context data, and displays related files in real-time, eliminating the need for manual identification and central data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all files are stored on a central electronic data repository, then data relationships can be monitored, but processing power requirements and costs increase significantly
Solution Approach 1:
The patent divides the centralized data storage system into multiple distributed electronic data repositories. Each repository stores files independently, eliminating the need for a single central repository. The system segments the monitoring function by implementing periodic scanning at each repository level, reducing the processing burden on any single system component.
Solution Approach 2:
The patent implements periodic scanning of electronic data repositories instead of continuous monitoring. The system scans repositories at scheduled intervals to identify files and their relationships, which significantly reduces processing power requirements compared to real-time continuous monitoring while still maintaining effective data relationship tracking.
2Loss of information
If users manually identify relationships between data components, then data context can be established, but user burden and negative user experience increase
Solution Approach 1:
The patent enables the system to automatically identify and establish relationships between data components through periodic scanning and AI model execution. The system self-services the context establishment function by autonomously analyzing files, their metadata, and access patterns to determine relationships, eliminating the need for users to manually tag or designate connections between files.
Solution Approach 2:
The patent replaces the manual mechanical process of user-driven file relationship identification with an automated computational system. An artificial intelligence model analyzes file content, metadata, and access patterns to automatically establish data relationships, substituting user manual work with automated intelligent processing.
3Adaptability or versatility
If conventional productivity systems store large volumes of data centrally, then all data can be accessed, but storage costs and inefficiency increase
Solution Approach 1:
The patent segments data storage across multiple electronic data repositories instead of consolidating all data in a single central repository. This allows organizations to use existing distributed storage infrastructure, reducing the need for additional centralized storage capacity while maintaining data accessibility through the periodic scanning and relationship identification system.
Data Source
AI summary
Described herein are methods and system for electronic workflow management having a central server that periodically scans data accessible to multiple computers and data interacted with by different users to generate a nodal data structure comprising of interrelated nodes where each node corresponds to a workflow component, such as files, messages, tasks, and the like. The server then executes various analytical protocols to identify and link/merge nodes corresponding to related content. Upon receiving an indication that a user is entering his/her time into a timekeeping software tool, the server traverses the nodal data structure, identifies a relevant project associated with the user's worked hours and displays a suggestion (e.g., identified project) for the user.