Double-loop learning
Double-loop learning questions the assumptions, objectives or decision rules behind a target rather than only adjusting actions to hit it. It is useful when the environment changes or a target drives harmful behaviour. It complements single-loop control and does not mean abandoning accountability. The organisation should explain why a governing assumption is being revised and distinguish learning from rewriting history to conceal poor execution.
Worked example
Repeated delivery targets encourage unsafe driving. Instead of only pressuring drivers to be faster, management reviews whether the target and incentive design are appropriate.
Common mistake
Revising a forecast number alone is not necessarily double-loop learning; the underlying objective or rule must be examined.
Where it appears in your exams
| Qualification | Exam | Relationship | Period |
|---|---|---|---|
| ACCA | APM | Supporting | September 2026–June 2027 |
| ACCA | PM | Supporting | September 2026–June 2027 |