Automated Project Management Using Conversational Processing
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Solution Overview
Problem
Existing project management systems fail to effectively track and manage transition states in agile-waterfall hybrid models, leading to inefficiencies and defects due to untracked changes and manual adjustments in project acceptance criteria.
Innovation Solution
The implementation of epic transition states in an information processing system, which automatically tracks and manages incremental changes across releases by monitoring discussions and inferring intents from stakeholder conversations, allowing for the creation and tracking of transition states and recommending acceptance criteria adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual tracking of project acceptance criteria is used, then flexibility in project management is maintained, but tracking accuracy and reliability deteriorate due to untracked changes
Solution Approach 1:
The system automatically monitors stakeholder conversations and self-updates transition state data without requiring manual intervention. The automated project management system extracts transition state information directly from conversation data, eliminating the need for manual tracking while maintaining flexibility in how projects are managed.
2Measurement precision
If automated tracking of transition states is implemented, then tracking precision and reliability improve, but system complexity increases
Solution Approach 1:
The system introduces a conversation data structure as an intermediary layer between stakeholder discussions and transition state tracking. This intermediary automatically captures and structures information from unstructured conversations, enabling precise tracking without requiring complex direct integration with all communication channels.
Solution Approach 2:
The system segments the project management tracking into discrete transition states that can be independently monitored. Each transition state represents a specific change in acceptance criteria, allowing the system to track precise changes without overwhelming complexity by breaking down the overall project state into manageable segments.
3Adaptability or versatility
If manual adjustments to acceptance criteria are made, then adaptability to changing requirements is maintained, but information loss occurs due to untracked changes
Solution Approach 1:
The system implements continuous feedback by monitoring stakeholder conversations and automatically detecting when acceptance criteria change. This feedback loop ensures that all adjustments to requirements are captured and recorded in the transition state data structure, preventing information loss while maintaining adaptability to new requirements.
4Productivity
If conversational processing is used to automatically track transition states, then productivity improves through automation, but measurement precision may deteriorate due to inference accuracy
Solution Approach 1:
The system performs preliminary structuring of conversation data into a standardized data structure before extracting transition state information. By pre-processing and organizing conversation data with defined schemas and relationships, the system improves the accuracy of subsequent inference while maintaining automation efficiency.
Data Source
AI summary
Automated project management techniques are disclosed using conversational processing to generate project-based transition states in an information processing system. For example, a method generates a data structure representing a lifecycle of at least one goal of a given project, wherein the data structure comprises one or more transition states associated with the at least one goal, and wherein the transition states are automatically tracked against one or more time instances. The method then facilitates management of the given project based on the generated data structure.