awslabs / awslabs/aidlc-workflows
[Feature]: Rules and Guidelines - Business Metrics to be mapped in the plan
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Description
### Description
The AIDLC workflow steering rules should be enhanced to include mandatory capture of business and success metrics during the Inception phase (Planning).
Problem:
Currently, the AIDLC workflow does not enforce the definition of measurable success criteria during planning. This means changes whether greenfield or brownfield can proceed through design and implementation
without clearly defined metrics to validate whether the delivered changes achieve their intended business outcomes.
Proposed Change:
Introduce steering rules in the Inception phase that require the AI to:
1. Identify and document business metrics relevant to the proposed change (e.g., revenue impact, cost reduction, user adoption, operational efficiency)
2. Define measurable success criteria with specific targets and thresholds
3. Establish baseline measurements for brownfield changes so that impact can be compared pre/post-implementation
4. Specify how and when these metrics will be measured (tooling, dashboards, data sources)
Expected Outcome:
For every greenfield or brownfield change processed through the AIDLC workflow, there will be a documented set of business and success metrics that can be used to objectively assess whether the delivered changes
meet their intended goals. This creates accountability and traceability from planning through to post-delivery validation.
### Use Case
The AIDLC workflow steering rules should be enhanced to include mandatory capture of business and success metrics during the Inception phase (Planning).
Problem:
Currently, the AIDLC workflow does not enforce the definition of measurable success criteria during planning. This means changes whether greenfield or brownfield can proceed through design and implementation
without clearly defined metrics to validate whether the delivered changes achieve their intended business outcomes.
Proposed Change:
Introduce steering rules in the Inception phase that require the AI to:
1. Identify and document business metrics relevant to the proposed change (e.g., revenue impact, cost reduction, user adoption, operational efficiency)
2. Define measurable success criteria with specific targets and thresholds
3. Establish baseline measurements for brownfield changes so that impact can be compared pre/post-implementation
4. Specify how and when these metrics will be measured (tooling, dashboards, data sources)
Expected Outcome:
For every greenfield or brownfield change processed through the AIDLC workflow, there will be a documented set of business and success metrics that can be used to objectively assess whether the delivered changes
meet their intended goals. This creates accountability and traceability from planning through to post-delivery validation.
### Area
Inception phase rules
### Additional Context
_No response_
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Assessment
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