How to segment data for engagement surveys

Before starting a survey, an important thing to think about is how you will want to view the data. While it’s useful to see the results from a survey based on how the entire group has responded, it is usually important to also break the scores down by smaller groups. But which groups will be the most useful?

On the topic of employee engagement, there are many ways you may be considering breaking down the data, but with so many options it can be overwhelming. The good news is, a lot of research has been done already to determine which aspects of work are most related to engagement at work. 

Groups that are most related to engagement

Length of service

It is universally consistent that levels of engagement are higher in the first year of service. It is often explained as the “honeymoon effect” as they have just chosen to join an organization and therefore feeling more positive. Because of this, breaking apart the data by length of service allows you to look at those in their first year separately from the rest, therefore giving you a view of the “real” engagement scores from the average tenured employee. 

Note: It’s useful to break apart length of service into buckets of years. The most frequently used buckets are as follows: Less than 1 year, 1-2 years, 3-5 years, 6-10 years, 11-15 years, 16-20 years, More than 20 years

Management level

Most organizations have at least three levels of management: individuals contributors, mid-level managers, and c-suite. It’s important to remember that the group of individual contributors is the largest group and the closest to the customer, product, patient, etc. therefore looking at that group on it’s own can help point out issues with the largest and highest leverage employee group. The senior leaders of an organization also have a unique “view from the top” which often leads them to have a higher level of engagement. Being able to break apart these groups will give more insight into where you need to focus your efforts. 

Note: You may have more levels of management than the three listed here. That’s okay, but keep in mind the points above as it’s most useful to be able to separately view the “front line” employees data but also to hide the c-suite data. 

Department / Team

The feeling of being on a team is a strong driver of engagement, but the data shows that which team you are on makes a large impact. This is because of how teams are typically broken apart. First, the data proves that when a team leader is engaged the team itself is far more likely to be engaged than when the team leader is disengaged. By viewing the data by team, it can help spot areas where the team leader may be part of the problem. Second, the feeling of being on a team is so highly correlated to engagement because employees tend to be more engaged when they feel connected to their team. Because engaged employees are contagious, when teams are closely connected, it is more likely that the sentiments of the engaged employees will trickle into the rest of the team.

Note: For each company, this may be called something different. It could be a department, team, group, squad, division, or something else. What’s most important with this group is being able to see employees who work together most regularly.

Groups that are least related to engagement

Gender, Age, and Ethnicity

Given the focus on Diversity and Inclusion in the workplace today, it may be surprising to learn that gender, age, and ethnicity have little impact on engagement. That doesn’t mean that how each of these groups are treated at work doesn’t have an impact on engagement, but instead that simply being in a particular age bracket or a particular gender does not mean you are more or less likely to be engaged at work. 

Note: This is only the case for surveys relating to engagement. When considering breaking apart groups for topics relating to diversity, inclusion, fairness, and safety, many of these groups would likely prove useful to see data for separately. 

Combining Groups

Sometimes it may be useful to look at the intersection of two groups, such as a particular team, but only those who are individual contributors. In order to get this type of data, consider in advance which groups you’d like to see combined. By looking at Department + Length of service or Location + Department you may be able to get to groups that give you more useful data.