> For the complete documentation index, see [llms.txt](https://docs.talentmap.com/knowledge-base/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.talentmap.com/knowledge-base/managers-and-leaders/read-your-results/key-driver-analysis.md).

# Key Driver Analysis

If your group has at least **30 or more survey respondents**, you can access key driver analysis within the **snapshot report**.

Watch: Understanding Key Drivers. Video length: 1m29s. Narrated with an AI voice.

{% embed url="<https://vimeo.com/1242037713>" %}

This report provides some of the most important information for understanding your survey results. The most effective, impactful and successful post-survey efforts are focused efforts. It is best to identify a short list of issues to focus on over the ensuing months. If valuable time, money and other resources are spread across too many initiatives, the risk is not making much progress on any one issue. The key driver analysis helps to identify which issues will have the most impact on engagement.

The following chart is an example of a key driver analysis:

![](https://2153489382-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FXPT9x2nGbXVrpeQoz4Oz%2Fuploads%2F2n9ilHeRfsbB31yZUkMy%2Fmg-img-7.png?alt=media)

The key driver analysis displays the strongest drivers of an outcome (i.e. engagement or retention) to help you understand which organizational dynamics have the most impact on making employees feel connected to the organization, or can also identify the dimensions that have the strongest impact on employees thinking of staying or leaving the organization.

The key driver analysis uses a statistical technique known as correlation analysis and displays the correlations in a table. This is the first step in deciding which dimensions should be prioritized for action. Dimensions with the highest correlations will provide the biggest “bang for the buck” for increasing engagement. As a general rule, correlations of .60 or higher are very strong. Those between .40 and .60 are of moderate strength, and are still worth acting on when the score is low, declining, or below the benchmark. Correlations below .40 are considered relatively weak.

![](https://2153489382-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FXPT9x2nGbXVrpeQoz4Oz%2Fuploads%2Ffj7HrhJYimslBHqv5cqz%2Fmg-img-8.png?alt=media)

Once the strongest drivers are identified, the next step is to consider the overall percent favourable score, whether the score is declining since the last survey and how the score compares to the benchmark. Strong drivers that have low favourable scores, are declining and/or are below the benchmark should be prioritized for action.


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