What are Noise, Bias, and Signal?
Noise, Bias, and Signal are about the quality and applicability of the information we use to make all decisions. When making decisions, especially important ones that can dramatically impact our professional lives, we want to ensure that we are receiving and generating information signals. We don’t want to receive or generate information flows that are biased or noisy. Don’t worry; I will explain these three terms quickly below.
Signal Information Flows comprise highly relevant and clear data directly related to the question, project, or issue at hand. In this situation, we would say that the information is high quality and of high applicability.
Noisy Information Flows are comprised of data that are all over the place without a clear pattern making it impossible to apply it to anything accurately. Imagine throwing a bunch of marbles on the floor. Over many tries, you won’t be able to predict where the marbles will end up with any valid insights from the previous throws. You may think you see a pattern (false signal) but in reality, it doesn’t exist, making any application of the pattern useless.
Biased Information Flows comprise data that are closely grouped but systematically incorrect. Imagine trying to hit a target at the gun range (only for this example), and the scope always puts you 10 inches from the bullseye in the same spot.
I invite you to read our section, Governing Dynamics: Noise, Bias, and Signal, with more detailed insights since we have a shared love for Signals and a desire to break up with our Noisy and Biased information flows. They’re just so unreliable!
