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AI Impact Assessment

Introduction

The AI Impact Assessment Widget for IBM DOORS Next is a powerful tool designed to streamline the evaluation of requirement changes and additions within your project modules. This widget uses AI to analyze the content of your existing modules and deliver structured, well-reasoned decisions on the impact of proposed changes. With features for automatic conflict detection, batch processing, and support for large-scale modules, the AI Impact Assessment Widget helps teams make faster, more confident decisions on requirement evolution directly within the DOORS Next environment.

Problem Statement

Challenges with Assessing Requirement Change Impact

Assessing the impact of requirement changes and additions in IBM DOORS Next is often a manual, time-consuming process that relies heavily on the reviewer's judgment and familiarity with the module.

The default DNG tools do not provide automated support for detecting conflicts or redundancies introduced by new or modified requirements.

Undetected inconsistencies can go unnoticed until later in the project lifecycle, increasing rework and risk.

Evaluating large batches of changes, such as those delivered via Excel change requests, against potentially thousands of existing requirements is impractical to do manually.

These challenges make it difficult for teams to maintain consistency and traceability while keeping pace with the volume of changes typical in large-scale projects.

Solution

Accelerating Impact Analysis with AI-Driven Decision Support

The AI Impact Assessment Widget solves these issues by using AI to automatically analyze the impact of requirement changes and additions against your existing module content. Users get structured decisions backed by clear rationale, along with proposed improvements to requirement text and placement, all within the DOORS Next environment.

Key Features

Conflict and Redundancy Detection - Automatically detects conflicts and redundancies introduced by new or changed requirements across single or multiple modules.
Structured Decision Output - Delivers structured decisions with clear rationale, making it easy to understand why a change was accepted, flagged, or rejected.
Batch Processing - Processes Add, Change, and Remove requests from an Excel file all at once, enabling efficient handling of large volumes of changes.
Scalability for Large Modules - Supports large modules with 10,000+ requirements through Retrieval-Augmented Generation (RAG), ensuring reliable analysis even at scale.
Requirement Text and Placement Suggestions - Proposes improved requirement text and suggests the exact placement for new or revised requirements within the module.

Benefits

Faster Decision-Making - Reduces the time needed to evaluate the impact of requirement changes, enabling teams to move faster and with greater confidence.
Improved Consistency - Helps maintain consistency across the module by identifying conflicts and redundancies before they are introduced.
Efficient Handling of Large Changesets - Streamlines the review process for batch changes submitted via Excel, saving significant manual effort.
Reliable Performance at Scale - Ensures accurate, reliable analysis even in large modules containing thousands of requirements.
Higher-Quality Requirements - Supports better requirement writing and placement, contributing to more professional and well-structured documentation.