Recently on the Insights blog we discussed some hard evidence on employee engagement and how it can have real bottom-line impact on an organisation.
This is great to know, but of course, we can’t work to improve engagement if it’s not measurable. This is likely why many organisations haven’t been able to prioritise engagement in the past.
Luckily with the technology available today, tools like sentiment and keyword analysis and automated continuous feedback to measure employee engagement are extremely accessible. Now every organisation can be empowered to understand how engaged their employees are, and work to improve engagement over time.
The following HR tools can be used to gather and interpret employee engagement data, but more importantly, show you the root causes of these results so you can act on them.
In order to get insights out, you need to first capture the right information. Having a Continuous Feedback process in place to take input from employees on a monthly basis will provide far more relevant insights than an annual employee engagement survey.
By sending a quick pulse form to staff each month to see how they are going, you can give your people the opportunity to give feedback on things like how they are progressing towards their goals, if they need additional training, what they been achieving, and more. These answers help to identify areas that may be adding or detracting from engagement levels.
Of course, it’s one thing to have this information available, but how can these large sums of data be effectively analysed and understood? This is where analytics tools come into play.
Happiness Analytics is one analytics tool offered through intelliHR that will help to breakdown and understand the insights gathered through continuous feedback, so action can be taken.
Through your continuous feedback pulses, include a question asking employees to rate their happiness in their role on a scale from 1-10 (10 being the happiest). Under the Happiness Analytics dashboard in intelliHR, you’ll then be able to track average happiness over time, and break down happiness scores among different teams, business units, pay grades, locations and more.
Here we can see that the IT department was having a consistent drop in happiness ratings from August through to October but then saw considerable uplift in November! Later in this blog we’ll look further into how the reasons behind this can be identified.
Asking employees to rate their happiness is one simple question that staff can answer in a single click, but it gathers a whole host of invaluable insights. You’re able to learn what is making your staff happy or unhappy, identifying trends and sudden changes, and determining the root causes to fix them.
To take Happiness Analytics one step further, we can also look at Happiness Keywords. The Happiness Keywords tool uses AI to analyse responses from employees, highlighting significant words or phrases that are impacting on happiness levels in your organisation. This not only helps leaders to understand the causes impacting on happiness, but also manage them proactively.
Revisiting our earlier example on the IT department, let’s look at Happiness Keywords to see what common themes may be behind the recent uplift in overall happiness.
In this case, the Happiness Keywords tool has shown us that happiness recently increased thanks to the energy from a recent influx of new starters joining the team.
Another measure of employee engagement can be how people are progressing towards their goals. Consistent stagnation or lack of progress could signal disengagement while a cohort that’s hitting their goals again and again is a good sign of an engaged and motivated workforce. After all, engaged employees are 31% more productive, according to the University of California.
When tracking goals in intelliHR, you’ll have automatic access to analytics dashboards breaking down goal performance across teams, supervisors, location and more. In this example, we can see that goal progress is lagging behind, and this could be a sign of suffering engagement rates, which can be investigated by looking into continuous feedback responses to determine reasons behind this. Another area where these reasons can be identified in intelliHR is in the goal comments section. Every goal set in this system has a comment thread section where managers and their direct reports can liaise on how goals are going and uncover any roadblocks that could be affecting this.
But what about large organisations or big teams? It’s just not always possible to manually read through all goal comments or all feedback responses for every single employee.
The good news is simply, you don’t need to do that at all. Which is where our next tool comes in.
Historically it has always been relatively simple to analyse large chunks or quantitative data like a happiness rating from 1-10, but finding trends in qualitative data like written responses on surveys wasn’t always as easy. This is now possible with the growing accessibility of Artificial Intelligence (AI) and one way intelliHR has harnessed this is through its Sentiment Analysis tool.
Sentiment analysis uses AI to determine the emotional tone behind different words and phrases in what employees are saying in continuous feedback, goal comments, performance management records, diary notes and most other forms completed through the system.
Sentiment is one measure of employee engagement in that it shows how positive or negative staff are feeling as well as exposing the root causes of this. In this example, we can see trends in average employee sentiment over time.
It’s also possible to drill down to the source data and see where these positive or negative scores have been measured from.
Now that you know how to measure employee engagement, you might also want to start thinking about employee experience. We recently explored this here on the Insights blog.
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