The Learning Loop is the basic structure of every iterative work process: act, observe, reflect, adapt — then start again. It describes how organizations and teams systematically learn from experience instead of repeating the same mistakes. The loop exists in various forms: as the PDCA cycle in quality management, as Build-Measure-Learn in Lean Startup, and as the OODA Loop in military contexts.
The critical distinction is between Single-Loop and Double-Loop Learning. In Single-Loop, behavior is adjusted while the underlying assumptions remain untouched — like a thermostat that regulates temperature. In Double-Loop Learning, the assumptions themselves are questioned: Are we even regulating the right temperature? A product team that only asks after each sprint “Did we deliver fast enough?” is practicing Single-Loop. A team that asks “Are we building the right thing?” is practicing Double-Loop Learning — and arrives at fundamentally different decisions.
The concept traces back to Chris Argyris and Donald Schon, who described Double-Loop Learning as a prerequisite for organizational learning. The biggest hurdle in practice: reflection requires time, and that time is not scheduled in most organizations.
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