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.

種類 ヒートマップエンジン echarts-heatmap更新日 2026/9/24

依頼内容

“Draw a heatmap correlation matrix for Beacon’s team survey: clarity, workload, manager support and growth opportunities.”

次はこちらChange workload versus growth correlation to 0.35.Add a note that correlations are not causation.

この図に含まれるもの

図の背後にある意思決定を読み解く。

01Set the scope

Use one reporting period and one clear unit.

02Read the pattern

Identify the largest concentration or directional change.

03Check the source

Confirm the displayed values against the underlying data.

Use this heatmap when the stated values and labels are the information the reader needs to compare.

ヒートマップのテンプレートをすべて見る →

よくある質問

What does this heatmap show?

A heatmap uses colour to show the size of a value at the intersection of two categories. It helps readers spot concentrations, gaps and repeated patterns quickly.

How should I read this heatmap?

Choose a colour scale whose minimum and maximum match the data, and include cell labels when precise values matter to the decision.

Can I adapt this heatmap example?

Yes. Replace the title, labels and values with your own data, then check that the prompt still describes every important element in the chart.