Implementation evidence
Procedure issued, tooling installed, software released, training completed, drawing changed or purchase requirement updated. Necessary, but normally insufficient alone to prove effectiveness.

A practical decision model for establishing whether a permanent corrective action has actually broken the causal chain and can credibly support corrective-action closure or an 8D D6 close-out. The app separates implementation evidence from effectiveness evidence, selects verification methods proportionate to risk, challenges the action through walk-throughs, talk-throughs and thought experiments, records physical and objective evidence, checks sustained performance, and produces an auditable verification report.
Procedure issued, tooling installed, software released, training completed, drawing changed or purchase requirement updated. Necessary, but normally insufficient alone to prove effectiveness.
Challenge test passed, process or product result demonstrated, causal parameter controlled, recurrence absent across meaningful exposure, or comparable evidence showing the unwanted effect is prevented.
Reconstruct the original event and ask: if this corrective action had existed then, would it have prevented the event? If not, the action may not address the verified cause.
Deliberately introduce the initiating error where safe and practical. A robust control should detect, prevent or contain the error before the original unwanted effect occurs.
Immediate success can show capability. Sustained evidence shows the correction continues to operate under representative production, shifts, people, equipment, suppliers or conditions.
For significant problems, effectiveness should not rely only on the person who implemented the action. Independent review increases confidence and reduces confirmation bias.
Observe the real process from start to finish and ask where the new control prevents the original causal mechanism.
Give personnel a realistic scenario and ask them to explain exactly what they would do without leading them to the expected answer.
Use a hypothetical but realistic condition to test whether the corrected system logically prevents recurrence, especially for rare events.
Replay the original event with the new control inserted. Identify the exact point at which the causal chain should now be broken.
Where safe, deliberately introduce the original initiating error or an equivalent error and confirm that the control detects or prevents it.
Test the product, process, assembly or system under representative conditions and compare results with predefined acceptance criteria.
Verify the causal process characteristic is controlled through parameter records, capability, trend data, alarms or other objective measures.
Compare defect rate, escape rate, process result or other relevant metric before and after implementation with meaningful exposure.
Sample representative work after implementation across relevant lots, shifts, operators, machines, products, suppliers or dates.
Verify changed requirements are deployed and records show the new control is used. Strong for implementation; usually pair with outcome evidence.
Confirm the people performing the work understand the change, its purpose, abnormal-condition response and escalation route.
Where relevant, use customer, test, field or downstream process evidence to confirm the original unwanted effect is no longer present.
| Level | Typical evidence | Interpretation |
|---|---|---|
| 1 · Administrative | Procedure revised, training record, action marked complete | Shows implementation; weak proof of effectiveness on its own. |
| 2 · Demonstrative | Talk-through, interview, controlled walk-through | Shows understanding and plausible operation; useful for low/medium risk or as supporting evidence. |
| 3 · Objective | Observed process, sampled records, measured output, before/after data | Direct evidence that the corrected process is operating and producing the intended result. |
| 4 · Challenged | Fault insertion, counterfactual replay, representative functional/environmental test | Strong evidence because the correction is deliberately tested against the failure mechanism. |
| 5 · Sustained / systemic | Meaningful exposure over time, multiple lots/shifts, systemic deployment, downstream confirmation | Highest confidence that the correction remains effective and is not a one-off success. |