Signal Distortion

It describes the breakdown of accurate information flow within a system. When signals are altered — through noise, suppression, bias, or misinterpretation — the system loses the ability to respond to its actual conditions. A manager who only hears good news because bad news gets filtered out at every level of a reporting chain isn't managing a healthy team; they're managing a system that has quietly lost the ability to tell them what's actually happening. Decisions made from that filtered picture don't fail randomly — they fail in the specific direction the distortion was already pointing, which then reinforces whatever produced the distortion in the first place.

This tends to be invisible from the inside. Perception depends on whatever signal is actually available, so a system rarely experiences its own information as compromised — it experiences its interpretation as simply what's true. That's what makes it hard to correct without something from outside the system: an external reference point, an audit, a person willing to say what the filtered channels won't.

This is why feedback alone doesn't guarantee correction. A system can be flooded with information and still act on a false picture, if what's flowing through it has already been filtered, softened, or misread before it arrives. Restoring coherence in a case like this isn't about gathering more data — it's about restoring the integrity of the channel the data is traveling through, so what the system is responding to actually matches what's happening.