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Peakon
Last Updated: 2025-11-28
Concept: Historical Data

Concept: Historical Data

Historical data remains on the dashboard, but it might no longer be part of the rolling current score depending on your company’s data visibility settings as new surveys roll out.
You can switch to a previous survey round or compare current scores with scores from earlier rounds. Score aggregation settings apply to historical data, but the visibility period starts from a different point in time.
Administrators also have the ability to delete historical survey data, including employee scores and comments, for specific survey rounds. Visit Delete Historical Survey Data for steps.
Method
Description
Considerations
Viewing a previous round
If your dashboard contains multiple survey rounds, you can switch your dashboard to a previous round.
  1. Open the context switcher.
  2. Expand
    Settings
    and select
    View previous round
    .
  3. Select a survey round.
The
View previous round
feature doesn't support these features and pages:
  • Focus areas and strengths.
  • Focus segments.
  • Shared dashboard.
  • Curated Insights.
  • Action planning.
  • Improve section.
  • Administration section.
  • PowerPoint export.
  • Impact feature.
If you have multiple survey rounds ending in the same week, the historical round picker displays the latest round of the week. The selected round contains aggregated data up until the end date of the selected round. In this context, a week is Monday to Sunday.
If the selected round somewhat overlaps with another survey round, the other survey's data doesn't contribute to the selected round if its soft close date is after the selected round's soft close date. Example: Filtering by a survey round in the Company context when a specific business unit had a targeted standalone survey that closed days after the selected survey round.
On Heatmaps analysis for each question set, you can view information on the
Round end
dropdown menu that enables you to view whether your selected question set was included as part of the survey round. On the
Round end date
you can also view when you select a previous survey round that didn't contain the selected question set.
Your access control group determines which previous rounds you can view. You can also hide Onboarding and Exit survey rounds from the selected view.
Score over time graph
If your dashboard contains multiple survey rounds, you can expand the
Score over time
graph to display:
  • Aggregated score.
  • Benchmark.
  • NPS distribution.
The benchmark displays in quarterly increments, based on when Peakon updates its benchmarking data.
The graph only displays the survey rounds that contain questions from the question set that you're viewing.
Comparison to a historical survey round
You can set your heat map to display a score comparison for your subsegments.
  1. Go to
    Analysis
    Heat map
    .
  2. Click
    View
    , then
    Diff. to round
    .
  3. Select a survey round for comparison.
If a score comparison isn't available for a segment, it's possible that:
  • The segment wasn't part of your dashboard at the selected point in time.
  • The segment had a confidentiality conflict at the selected point in time.

Data Deletion

Administrators can permanently delete historical survey data for specific employees and specific surveys, including employee scores and comments. You can delete data for one or more survey rounds and multiple employees at once. For steps, visit Delete Historical Survey Data.
Once you delete historical data, allow some time for the dashboards to reflect these changes. If a large amount of data is deleted, focus areas might initially appear incorrect and will need to be recalculated. Scores are likely to change, especially if a large volume of data is removed, though minor deletions (Example: 1 or 2 data points) won’t have much of an impact. Additionally, removing comments will affect related topics, which will also require recalculation. Our recommendation is to review your selections to avoid unintended deletions, as this process could lead to shifts in your data and require recalculation across various elements in your analysis.