Data cross-analysis helps to understand the differences in results among different groups of employees who share common characteristics and can be checked within the Heatmap.
Cross-analyses are always between the themes defined in the survey and other data available on the platform, such as area, department, level, etc. The more employee information you fill in on the platform, the more insights and possibilities you'll have for survey analysis.
To cross-reference this information, click the "Group" button and choose the category you want in the window that opens.
How to Analyze the Data:
In the example, the defined category was "Department," and the survey in question was answered by 67 employees:
Out of the 67 people who responded to the survey, we have:
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The Customer Success team with the highest score in the engagement theme, followed by the Sales and Engineering teams.
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The Customer Success team with the highest score in the market adaptability theme, followed by the Engineering and Sales teams.
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The Customer Success team with the highest score in the compensation and benefits theme, followed by the Sales and Engineering teams.
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Among the analyzed themes, the highest average is in compensation and benefits, followed by market adaptability and engagement.
About the Heatmap:
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The colors on the heatmap are defined with the criteria: darker green = better score, darker red = lower score. They are not associated with fixed and standard scores. It's important to pay attention to this point because dark green, for example, may not always indicate good results, but rather the best results within that group.
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Clicking on an average theme per group, the next page will not only provide details of the results for that group (e.g., Growth). The details will encompass all the results of that theme in general
Which Cross-Analyses Are Most Recommended?
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Box quadrant/Evaluation score: Cross-analysis done to understand how groups of people grouped by "performance" in the evaluation perceive the company in the analyzed themes. For example, if high performers have a low average in the compensation theme, adjusting their salaries can help with retention. However, if they have a low average in the emotional well-being theme, offering a differentiated benefit or, if the problem is workload, bringing more people into the team can aid in retention.
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Area/Department: Cross-analysis done to understand how teams perceive the company in the analyzed themes. For example, if Team A has a low average in the leadership theme while Team B has the highest average in that theme, facilitating a mentoring session among the leaders can help with training.
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Level (seniority)/Position: Cross-analysis done to understand how different seniority levels perceive the company in the analyzed themes. For example, if the company's base has a basic average in visibility of the company's strategy, the OKRs methodology can be an excellent solution to address this issue.
Recommendations and Best Practices for This Type of Analysis:
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It's essential to be cautious when analyzing a survey to avoid making conclusions about groups that were not well represented in the survey. Therefore, before starting the analysis, it's crucial to check the participation rate.
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To facilitate the analysis, it's suggested that the groups created for data cross-analysis have up to 5 options. For example, if you choose the "Department" category, have at least five departments registered on the platform. An action that can be taken to help group categories with many options is to create an "other" option.
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When cross-referencing survey results with the 9-box or review results, it's essential to be careful not to compare if the results are very old and may not represent the company's current state.
🚨 IMPORTANT: If any employee field is updated during the survey, at the end of it, it's necessary to request a snapshot from the chat (an action that will update the data in the analyses).
To learn more about other analyses within the survey product, you can check out this article: How to find data to analyze the survey on the platform?
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