Results and Analytics

Analytics opens after summarizing results. It shows not only the average score, but a working picture: where the team feels stability, where there is tension, and which topics need to be discussed further.

Results are needed for the See stage in the cycle Ask → See → Discuss → Verify. Their purpose is not to find who is to blame, but to show what the team should work on.

Result levels

The platform calculates results at three levels: organization, team, and participant.

The organizational level shows the overall picture for the measurement: overall score, summary, strong areas and areas of tension. It helps the change initiator understand where the focus of the whole organization is.

The team level shows differences between teams. This is useful when in one part of the organization the process works consistently, and in another the same topic creates tension. Team analytics depends on the structure of teams and the selected survey audience.

The personal result helps the participant understand their own response. It is separated from management analytics: the personal picture does not turn into a control tool and is not mixed into the overall conclusions.

What is visible in the metrics

Scores show which way the state is moving, but on their own they do not explain the reason. Therefore, next to the numerical results, summaries, answer distributions, and semantic groups of similar comments appear.

Questions and categories help read the picture in layers. The category shows the general block of the topic, the question reveals the specific point of tension, and text summaries explain what is behind the score.

If there is a previous breakdown for the measurement, the platform shows the trend. The comparison helps understand whether the tension has gone away after working with growth points, or whether the chosen approach needs to be changed.

How the score is calculated

The measurement score is a number from 0 to 100. The platform calculates it as an average across the hierarchy, step by step:

1. Question score — the average rating of all answers to this question.
2. Category score — the average value across all its questions.
3. Overall score — the average across all categories.

This approach gives equal weight to topics. A category with ten questions influences the overall score the same as a category with two, and a question answered by two people carries the same weight in its category as a question answered by forty participants.

If no one answered a question, it does not lower the score but simply drops out of the calculation. Similarly, an empty category is not counted as zero but is excluded from the overall score.

If there are no answers at all, there is no score: the platform shows a dash rather than a zero. Zero would mean the worst possible result, while a lack of data is not a negative score, but rather the absence of data.

How to read analytics

Start with the overall result, but do not stop there. The average score may look calm even if a particular team or category has declined. The whole point of analytics is not to let a weak spot hide behind the overall figure.

Then look at teams, categories, and questions. If the same topic repeats in different places, it is a good candidate for discussion as a growth point. If tension is visible only in a narrow breakdown, it is also better to look for a solution closer to that breakdown rather than launching a general reform.

Text summaries should be read as a map of causes, not as verbatim quotes from participants. The platform protects the original answers and shows a generalized meaning.

Privacy boundaries

Raw answers are never shown to anyone. Analytics only ever draws on anonymized answers, aggregates, and summaries, and only when there is enough data for safe display.

Different thresholds apply to different details. List fragments are hidden when the number of answers is very small; distributions and semantic groups require a denser sample. If the threshold is not met, the platform does not show this breakdown or replaces it with a more general picture.

This limit is not a flaw in the report. It protects trust in the survey: participants can answer honestly, and the team works with the overall picture rather than trying to find out who said what.