“I Only Said One Thing” — Small Feedback, Big Effect

Team meeting. Anna points out that Maja has made the same kind of mistake twice that week.

— Maja, this is the second time we’ve had the same error. Please keep an eye on it.
— Okay.

A few days later, Maja speaks less and asks to leave the project. Anna starts wondering whether her public comment caused it.

What really happened

Anna sees two events in sequence: first she gave Maja public feedback; then Maja became quieter and wanted to step away from the project. A natural story appears: “I caused this.” That story may be true, but the sequence alone does not prove it. Maja may have several other reasons Anna knows nothing about. The important move is to separate the observation from the explanation. The observation is: her behavior changed after the conversation. The explanation is: it changed because of the conversation. The second claim needs more evidence.

What the research says

People readily explain others’ behavior from what they can observe and may give too little weight to situational factors or missing information — a pattern known as correspondence bias (Gilbert & Malone, 1995). In this scene, Anna has not fully fallen into that trap because she stops and considers alternative causes. There is also a basic logic principle worth keeping in mind: “after this” does not automatically mean “because of this” — the classic post hoc ergo propter hoc error. Establishing causality requires more than a sequence of events.

How to handle it

Start by separating two columns: “what I know” and “what I suspect.” Then test the hypothesis with the person involved: “I’ve noticed you’ve been speaking less since that conversation. I don’t know whether the two are connected. How do you see it?” That allows you to be empathetic without writing the other person’s story for them. The general rule is: a change in behavior is information; its cause remains a hypothesis until you have better evidence.

How Empatyzer and Em can help

Empatyzer is particularly useful when an observation can easily become an untested explanation. The assessment may show Anna that her management style creates a strong need to find a cause quickly and regain control, but Em should not confirm her theory about Maja without evidence. Instead, it can help her prepare a conversation that separates fact from hypothesis: “I’ve noticed you’ve been speaking less lately; I don’t know whether that is connected to the earlier situation — how do you see it?” Maja’s profile can help Em choose a way of asking that does not add unnecessary pressure. If similar reactions appear across a group, team-level data can provide broader context without guessing the reason for any one person. Micro-lessons reinforce the habit of checking an interpretation with the person before using it as the basis for a decision.