Task Flow Guidance System Reducing Trial and Error
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Solution Overview
Problem
Users often face difficulties in software-related tasks due to unsuccessful task flow paths, as they may not be aware of alternative decisions that could lead to better results, and existing technologies lack efficient methods to guide users back to optimal paths.
Innovation Solution
A system that identifies current task flow paths, compares them to historical data, and suggests alternative nodes based on data context and probability of success, providing users with scenario views and statistical information to inform their decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users follow task flow paths without guidance, then they can complete tasks independently, but they may end up on unsuccessful paths and waste time
Solution Approach 1:
The system provides feedback to users by detecting when they are on unsuccessful task flow paths and suggesting alternative paths based on historical data. This feedback mechanism helps users avoid time-wasting dead ends while maintaining independent task completion capability.
Solution Approach 2:
The system performs preliminary analysis of historical task flow data to identify successful paths before users encounter dead ends. By pre-computing and storing successful task flow patterns, the system can quickly suggest appropriate alternatives when users are on unsuccessful paths.
2Ease of operation
If the system provides continuous guidance and suggestions, then users can make better decisions, but the system complexity increases
Solution Approach 1:
The system automatically analyzes user actions and historical data to generate suggestions without requiring manual configuration or complex user input. The guidance system serves itself by autonomously learning from historical task flow data and adapting to user needs.
Solution Approach 2:
The system changes the parameter of information presentation by transforming raw historical data into simplified, actionable suggestions. This parameter transformation makes the guidance system easier to operate while managing complexity through automated data processing.
3Measurement precision
If the system analyzes historical task flow data, then it can provide accurate suggestions, but data processing and storage requirements increase
Solution Approach 1:
The system extracts only the relevant patterns and successful path information from the vast historical data, rather than processing every detail. This extraction approach maintains high suggestion accuracy while reducing the effective data processing and storage requirements.
Solution Approach 2:
The historical data is segmented into meaningful task flow patterns and categories. By organizing data into segments based on task types and successful paths, the system can efficiently process and retrieve relevant information without handling the entire data volume at once.
Data Source
AI summary
A current task flow path of a user is identified based on task flow nodes of the current task flow path, and a data context of the task flow nodes. The task flow nodes may include actions performed by the user with one or more software applications. A suggestion point of the current task flow path is detected. The suggestion point may be detected based upon a user action indicating that the user needs assistance to proceed with the current task flow path. A candidate task flow node is selected responsive to a comparison of the current task flow path to historical task flows. A suggestion is displayed to the user based on the candidate task flow node.