At intelliHR we’re lucky to be able to help our customers with the collection of employee engagement and sentiment data, as well as helping them extract insights from this data and understand the dynamics in their business.
We wanted to take a look at the story the data was telling about employee wellbeing, sentiment and role satisfaction, and what businesses can take away from this experience and put into practice in the future. We compared year-on-year data from February to April 2019 and February to April 2020 to understand the impact the current crisis has had on employee wellbeing.
Before we go any further, it’s important to note that the data we reference below was aggregated from all users and does not include the individual or organisation source.
When we describe data, like the results from an engagement or employee wellbeing survey, we tend to focus on the average, or mean. Averages are certainly a useful way to summarise a dataset, but when focused on in isolation they can miss important and meaningful patterns.
To say “the average sentiment, or engagement score in Group A is higher than Group B” is helpful, but it doesn’t tell the whole story.
We compared year-on-year results from two data sets measuring employee satisfaction, one using self-ratings and the other using automated sentiment scores on qualitative data collected through our platform. We found that average employee happiness dropped in February through April this year compared to last. Not breaking any ground there, given the current climate, but there was more to the data. The decrease was significant (from a statistical perspective) but it was small – 8.14 down to 7.96 on a scale out of 10, which is about 2%. But would we be right then in saying that the recent crisis has had hardly any impact on employee happiness? Not quite, let me explain why.
Across our samples of self-reported happiness ratings, we saw an increase in variance of about 16% year on year. For those non-data minded folk, variance is a measurement of the spread between numbers in a data set. That is, it measures how far each number in the set is from the mean and therefore from every other number in the set. So, although the average happiness hardly moved, the actual ratings of employee happiness from check-in surveys post the COVID-19 outbreak were significantly more variable than at the same time last year.
High variance in your data means responses are more spread out rather than concentrated around the average. This indicates that while some employees actually coped better in these uncertain times, more employees than usual also scored much lower on happiness ratings and sentiment collected.
High variance in employee happiness and sentiment means the best response for the business would be to adopt varied approaches when communicating and supporting different target groups. Now is a great time to consider qualitative feedback data alongside quantitative data, look for common themes that are causing concerns for people. Similarly being able to understand the positive themes within your business may provide guidance about what messaging to focus on.
So, in uncertain times how do you pick up on those employees that aren’t coping so well and ensure they get any extra support they need?
Employee wellbeing and happiness can be a tough thing to measure. We use analytics to take the pulse of the organisation and identify patterns that might represent opportunities for improvement but sometimes the patterns that exist across a business unit may hide meaningful changes in the individual. When we’re looking at something like happiness, it’s important to remember that there’s a human on the other side of each data row.
We recognised that when asking employees to self-report their current state of happiness and wellbeing, that even on a simple rating scale, one individual’s 7 or 8 is very different to someone else’s. Therefore, what’s actually more meaningful than recording an average happiness score across a large group is understanding when an employee varies up or down from their individual baseline happiness. We enhanced our employee happiness analytics to do just this, and calculate a baseline profile for each employee based on historical responses. Now each time an employee responds to a new check in, the variance from their baseline happiness is recorded and makes up the core of our employee happiness analytics.
People and Culture teams and business leaders can filter responses where a happiness rating moved downwards, below the employees’ baseline. An employee may self-report an 7 out of 10 for role satisfaction. If only focusing on group averages, a score of 7 might look normal, not cause for concern. However for that employee, a score of 7 might represent a downward movement. Our new happiness analytics helps HR teams and managers identify these important movements, and where needed spark meaningful, human conversations.
If you’d like to get more insights into how your team is feeling and coping during these times, get in touch.