Team survey correlation heatmap
Beacon’s people-analytics team uses a correlation heatmap to compare four survey measures at once. The diagonal cells are one because each measure is perfectly correlated with itself; the off-diagonal values indicate the direction and strength of the observed relationships. The chart helps reviewers locate relationships worth investigating, such as manager support and growth opportunities. It does not establish a causal explanation, and small or unrepresentative survey samples can make a colour pattern look stronger than it is. Before sharing it, compare the chart with the source table and make the scope explicit. A clear date range, population and unit help another reader interpret the pattern correctly and decide whether follow-up analysis is needed.
Open it in the AI editor with a prompt pre-filled — keep what works, change what doesn't.
Scenario
Team survey correlation heatmap is prepared for a focused review.
Key decisions
- Set the scope: Use one reporting period and one clear unit.
- Read the pattern: Identify the largest concentration or directional change.
- Check the source: Confirm the displayed values against the underlying data.
When to reuse this
Use this heatmap when the stated values and labels are the information the reader needs to compare.
Frequently asked questions
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