Single- and Double-Loop Learning: Decide Whether to Fix the Action or the Rule

Communication · Executive Insight Brief · 229

The next fix may protect the same failure

Single and Double Loop Learning separates correction within existing assumptions from inquiry that makes the assumptions themselves revisable

Premise

Organizations can correct the same problem repeatedly while preserving the condition that causes it. Single-loop learning changes an action to restore performance under existing goals, policies, or decision rules. Double-loop learning asks whether those governing variables should themselves change. The distinction prevents leaders from treating every recurring mismatch as an execution failure.

Argyris and Schön developed the lineage through their 1974 work on theories of action and their 1978 organizational-learning formulation. Their contribution is not a slogan about thinking more deeply. It is a disciplined separation between improving action under a sound rule and examining whether the target, assumption, value, or policy that defines the correction is part of the problem.

What the model is: Single- and Double-Loop Learning in Knowledge →