Success Metrics¶

Library AreaTemplate Library

Current PageSuccess Metrics

FocusSuccess evidence

UseDefine measurable outcomes and trust indicators

Repository Areadocs/template-library/vision/

← Previous Assumptions

Current Success Metrics

Next → Vision Readiness Summary

Template purpose¶

Use this template to define what success should mean before requirements are written.

Success metrics should include not only business or user outcomes, but also operational indicators, trustworthiness signals, adoption evidence, and conditions that would show the project did not succeed.

Project¶

<Project name>

Document control¶

Field	Value
Artifact owner	`<owner>`
Primary reviewers	`<reviewers>`
Status	`<draft / in review / accepted / revised>`
Last updated	`<YYYY-MM-DD>`
Related Engineering Stage	`ES-101 — Vision and Problem Definition`
Project workspace target	`docs/project-workspace/vision/success_metrics.md`

Success summary¶

Describe what success means for this project.

<Brief success summary.>

Outcome metrics¶

ID	Metric	Target or Direction	Evidence Source	Review Timing
OM-001	`<metric>`	`<target / threshold / direction>`	`<source>`	`<stage, milestone, release, pilot, operations>`

Operational metrics¶

ID	Metric	Target or Direction	Evidence Source	Owner
OPM-001	`<availability, latency, support response, incident rate, recovery, throughput, service quality>`	`<target>`	`<monitoring, logs, support records, incident records>`	`<owner>`

Trustworthiness metrics¶

ID	Metric	Target or Direction	Evidence Source	Trust Dimension
TM-001	`<metric>`	`<target>`	`<source>`	`<reliability / safety / transparency / human oversight / accountability / privacy / security / fairness / auditability>`

AI-specific metrics¶

Use this section if AI is part of the system or materially part of the engineering workflow.

ID	Metric	Target or Direction	Evidence Source	Human Review Required?
AIM-001	`<accuracy, usefulness, hallucination rate, review acceptance, unsafe output rate, escalation rate, override rate, prompt stability>`	`<target>`	`<evaluation record, AI use log, review record, monitoring>`	`<yes / no / conditional>`

Adoption or usability indicators¶

ID	Indicator	Target or Direction	Evidence Source
AU-001	`<indicator>`	`<target>`	`<source>`

Learning and stewardship indicators¶

ID	Indicator	Target or Direction	Evidence Source
LS-001	`<feedback captured, incidents reviewed, lessons learned created, backlog updated, ownership assigned>`	`<target>`	`<stewardship record, incident review, monitoring summary, backlog>`

Negative success criteria¶

List outcomes that might look positive but would not satisfy the vision.

ID	False Success Signal	Why It Is Not Enough
NS-001	`<example: users click more often>`	`<reason this does not prove success>`

Metric risks¶

Risk	Impact	Mitigation
`<metric could be gamed, misleading, unavailable, biased, incomplete, or too expensive to measure>`	`<impact>`	`<mitigation>`

Review checklist¶

[ ] Success is defined before requirements are written.
[ ] Outcome, operational, trustworthiness, and adoption indicators are included.
[ ] AI-specific measures are included if relevant.
[ ] Evidence sources are identified.
[ ] False success signals are named.
[ ] Metrics can support later readiness and stewardship decisions.

Continue to Vision Readiness Summary

Summarize the ES-101 package and decide whether requirements work can begin.

Open Readiness Summary →