A feedback loop involves four distinct stages. First comes the data: A behavior must be measured, captured, and stored. This is the evidence stage. Second, the information must be relayed to the individual, not in the raw-data form in which it was captured but in a context that makes it emotionally resonant. This is the relevance stage. But even compelling information is useless if we don’t know what to make of it, so we need a third stage: consequence. The information must illuminate one or more paths ahead. And finally, the fourth stage: action. There must be a clear moment when the individual can recalibrate a behavior, make a choice, and act. Then that action is measured, and the feedback loop can run once more, every action stimulating new behaviors that inch us closer to our goals.
This basic framework has been shaped and refined by thinkers and researchers for ages. In the 18th century, engineers developed regulators and governors to modulate steam engines and other mechanical systems, an early application of feedback loops that later became codified into control theory, the engineering discipline behind everything from aerospace to robotics. The mathematician Norbert Wiener expanded on this work in the 1940s, devising the field of cybernetics, which analyzed how feedback loops operate in machinery and electronics and explored how those principles might be broadened to human systems.
-- Thomas Goetz from Harnessing the Power of Feedback Loops, Wired Magazine, June 2011
