'Drivers' of Employee Engagement?
Updated: Mar 4
Drivers of employee engagement?
Survey platforms identify what is claimed are ‘drivers’ of engagement. They are intended to provide HR and mangers with important data on where to direct their efforts if they are to improve engagement.
Unfortunately, these results are based on a rather simplistic analysis of the data, basically employing tests of relationships such as Pearson or Spearman correlations. This can provide an incorrect analysis and send your leaders off in the wrong direction. The use of such a simplistic assessment of the ‘drivers’ leads to incorrect assumptions for a variety of reasons, but are generally based on how the various scales and items have been developed, the absence of a sound theoretical framework underpinning the scales, the way in which the items are interrelated, as well as how the scores on items are distributed.
An example for a recent engagement survey can shed light on the issues. The engagement scale was made up of seven questions in the survey. If we simply look at the correlations in order to identify the ‘drivers’ of engagement, we find the following differences when compared to a more sophisticated analysis employing structural equation modelling.
(The strength of the driver from the simple correlation is shown first, followed (in parenthesis) by the strength of the driver following a more sophisticated analysis.)
Not only do the key drivers change, we can see how little impact the original drivers are having on engagement once a more comprehensive analysis is undertaken.
We need to be aware of the way in which the results from surveys are interpreted as action planning is likely to be undertaken on the basis of false assumptions. If we are going to spend money on better understanding staff, then we need to be confident that we understand what the data is actually telling us. It’s too easy to be blinded by the impressive colourful interactive dashboards, and it’s a little boring to delve into the statistics behind these interactive charts.
Dr P. Amanda Harris