Contents
How do you manage anonymity?
Betterworks Engage works with companies globally to ensure anonymity by controlling data visibility while allowing for segmentation and trending. A unique identifier is assigned to each response, and all data is hidden until each segment meets the 'anonymity threshold'. The 'anonymity threshold' ensures that no one in the organization can drill down to individual results or alter data in a way that removes respondent anonymity. This gives participants complete anonymity in their responses and ensures that their responses cannot be tied to their identity.
Betterworks Engage sends unique, encrypted survey invites to ensure employees can respond once and only once. Betterworks guarantees anonymity to more the 150,000 employees around the world. In reporting, no individual results are ever attached to a name or identity as the reports are always aggregated and anonymized.
Anonymity thresholds are in place throughout reporting to ensure that no respondent’s anonymity is compromised due to small segment sizes or low participation.
Total Respondents
Betterworks Engage admin users can set their organization’s anonymity threshold in the App Settings. This number can be no lower than three (3).
For instructions on how to set the anonymity threshold, see this article.
When viewing survey results, If the number of respondents for any segment is lower than the anonymity threshold, the user will see a message stating “Data cannot be displayed to ensure anonymity.”
Segment Level (Preventing Inference)
When viewing/comparing multiple segments side-by-side, additional data protections are in place to prevent users from deducing the responses in a segment that does not meet the anonymity threshold. This is based on the anonymity threshold and the number of respondents in subsequent segments.
If there are any segments within a dimension that are below the anonymity threshold, segment data is hidden starting with the smallest segment until the total number of hidden respondents is greater than the anonymity threshold. If that occurs, the following message will appear:
The Anonymity threshold is equal to X. The current visualization contains enough voters (X), but is filtered to prevent inference of XYZ segments.
Examples #1
Category results segmented by Location. Anonymity threshold is set to three (3).
- Charlotte: 12 respondents
- Sydney: 7 respondents
- Beijing: 2 respondents
The data for both Beijing (2) and Sydney (7) are hidden to bring the total number of hidden respondents above the anonymity threshold (3).
If only one segment was hidden (Beijing), it would be easy to infer (by comparing to org-wide data) which survey responses came from the individuals in the Beijing location. To help protect the anonymity of these 2 respondents, the second lowest segment (Sydney) is also hidden. This brings the total number of hidden respondents (9) to a number greater than the anonymity threshold of three (3).
Example #2
Category results segmented by Location. Anonymity threshold is set to three (3).
- Charlotte: 12 respondents
- Sydney: 2 respondents
- Beijing: 2 respondents
The data for both Beijing (2) and Sydney (2) are hidden. Since neither meets the anonymity threshold, the message does not appear.
If both Sydney and Beijing each have 2 respondents, there is no need to also hide Charlotte since the total number of hidden respondents (4) is already greater than the anonymity threshold of three (3).
Example #3
Category results segmented by Location. Anonymity threshold is set to three (3)
- Charlotte: 12 respondents
- Sydney: 4 respondents
- Beijing: 3 respondents
No segments are hidden because all segments meet or exceed the anonymity threshold.