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A meeting about a report for senior management. Tomasz brings Anna a detailed analysis.
— Tomasz, don’t go into that much detail. I need the decision.
On the next topic, he brings a short summary.
— This is too shallow. Where are the assumptions?
Anna is reacting to two different cases. Tomasz is trying to infer one permanent rule from reactions that were never explained as a rule.
How does Empatyzer help choose the right level of detail?
Empatyzer helps you see that the same boss may sometimes want a shortcut and sometimes want details. It also allows you to see how to determine the level of information by decision, not person.
Features that can help:
- Comparison: Compares your preferences in areas such as the level of detail, context and purpose of the decision, making it easier to separate the difference in style from ill intent in a "too much detail, too little" situation.
- Tips: Offer practical guidance for the situation "Too many details, sometimes too few": what to say directly, what could be misunderstood and how to conclude the conversation with clear next steps.
- Talk to Em about a specific person: It helps practice a conversation with a selected person in the situation "One too many details, one time too few" and check how the same message may sound in this relationship.
What really happened
Tomasz receives two messages from Anna that appear to contradict each other. First he hears that his report is too detailed, so the next time he cuts it down heavily. Then he is told the material is too shallow. He is trying to build a stable rule from two corrections, but he does not know the criterion Anna uses in different situations. From her perspective, the expectation may be perfectly consistent: one decision needs only the conclusion, while another depends on the assumptions. Tomasz cannot see that rule. After several experiences like this, it is easy to start thinking “I’m always getting it wrong,” even though the real problem is the absence of a shared standard for choosing the required depth.
What the research says
Feedback is most useful when the recipient can turn it into action. “Too much” or “too little” does not tell someone how to recognize the right level next time. Research on feedback shows that its effectiveness depends partly on content, credibility, and whether it provides usable information for changing performance. Work on feedback specificity adds an important nuance: more detail is not always better. Highly specific feedback can improve performance on the immediate task while sometimes reducing independent learning and exploration (Goodman, Wood, & Hendrickx, 2004). Tomasz’s problem is therefore not that he always needs more detailed instructions. He needs an explicit criterion for choosing the level of detail — in other words, greater role clarity around the output.
How to handle it
A useful solution is a fixed skeleton with variable depth. For example: page one always contains the recommendation, the three most important reasons, and the risks; detailed assumptions come later when the topic requires them. Anna can also frame the assignment explicitly: “Here I only need the recommendation,” or “Here the decision is meaningless without the assumptions.” The general rule is: a good standard does not tell people how much they must always write; it tells them how to recognize when the situation calls for more and when it calls for less.
How Empatyzer and Em can help
Empatyzer can help Anna and Tomasz escape the frustrating “too much / too little” cycle by showing that their difference lies mainly in how they calibrate information to the decision. Tomasz naturally wants to build a complete, coherent picture; Anna filters quickly for what is needed to act in the moment. Before an assignment, Em can ask Anna about the decision the audience needs to make and translate that into a clear criterion for Tomasz: “Page one: recommendation, three reasons, risks; details in the appendix,” or “No decision here without the assumptions.” Tomasz no longer has to reconstruct an invisible rule from successive corrections. Micro-lessons teach leaders to specify not only what must be produced, but also what decision it supports and at what level of detail. Over time, Empatyzer turns changing expectations into a more predictable way of working.
Sources
- Jodi S. Goodman; Robert E. Wood; Margaretha Hendrickx (2004). Feedback specificity, exploration, and learning. Journal of Applied Psychology, 89(2), 248-262. https://doi.org/10.1037/0021-9010.89.2.248 10.1037/0021-9010.89.2.248
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