As a people leader collecting continuous employee feedback, qualitative feedback in the form of comments from your people are a very rich source of insight and adds a lot of context to the quantitative responses. Peakon’s Topics analysis uses machine learning (Artificial Intelligence) algorithms to analyze employees’ comments and identify the important themes and issues that people care most about, while highlighting the sentiment of each Topic. See About Topics and how they work for more information about how the algorithms operate.
Viewing your Topics
Admins would almost certainly see topics at the global level first since they have access to all the data, however it may depends on the amount of comments that you have received so far. People leaders, with access to a dashboard and to view comments, would need to wait until they have on their dashboard roughly 200-300 comments related to an individual driver, value, or open-ended question before they would see topics appear.
To view your topics page
- Go to Topics within Insights.
- Click on Topics.
- Choose any relevant filter to view your topics. You can filter your topics by question sets.
Highlighted Topics (Dashboard view)
Peakon provides highlighted topics within your dashboards to help you understand where to focus your attention. There are five categories of highlighted topics:
- High Scoring - The topic with the highest average score. This informs managers of the aspects of work employees are most satisfied with.
- Low Scoring - The topic with the lowest average score. This informs managers of the aspects of work employees are least satisfied with.
- Most Comments - The topic made up of the most amount of comments. This informs managers of the themes that are on employees’ minds or of the most used words/language within employee comments.
- Consistent Comments - The topic made up of comments repeated in different survey rounds over time. This informs managers of the consistent themes coming through employee comments that are consistent over time.
- Comment Spike - The topic made up of a large number of comments within a short period of time. This informs managers of emerging themes from a one-time event or question.
Reviewing your Topics
Each topic available in the Topics page includes a summary of the most frequently mentioned points for that topic. The score assigned to each topic is an average of all scores for comments relating to that topic. This gives you an indication of the general sentiment towards that topic.
Topics can also be grouped into themes when the same words appear in topics. This allows you to quickly spot similarities as well as key differences in the topics identified.
There is a maximum of 3 themes per driver of engagement. If more than 3 themes are generated in a single driver, these will be displayed as single topics.
Example theme: "Personal Development".
Each topic contains an extract. The extract is a paragraph of the sentences that are most indicative of all the comments that make up a topic – giving you insight into a broad conversation in a few seconds.
Example extract: "I feel like my personal development has stalled in recent months … It feels like the personal development and career path of certain people is favoured."
In some instances, topics might not be helpful in understanding the themes from employee comments, or perhaps redundant topics have been generated. Removing a topic from the dashboard will add it to the exclude-list and will stop the word from being generated as a topic in the future. You’ll also be asked to provide feedback on the reason why a certain topic is being removed, to help train our algorithm in learning to generate more meaningful topics in the future.
Removing specific topics is possible in two ways:
- From within the driver topics list by clicking on the “x” icon.
- From the topic dashboard that shows its comments by clicking on the delete icon in the top right corner of your topic extract.
Considerations when removing topics
When removing a topic as an admin, it is removed from all contexts and manager views within Peakon.
When removing a topic as a manager, it is removed only from the manager’s view. This is to allow individual users the flexibility to focus on topics that help them interpret their employees’ comments.
Removing topics works across languages. As an example, if the word “feedback” is on the exclude-list in English but also appears as a topic in French, both will be excluded. This is only the case for exact words across languages.
Managing exclude-list topics
Exclude-list topics are managed from the topics overview page (scroll to the bottom of the page)
The exclude-list contains all the topics that have been removed
Removing a topic from this list allows the topic to be generated again from future survey rounds’ comments.
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