One of the greatest benefits of using a text-centric, exploratory approach to employee feedback is that you will identify issues that you’d never have thought about asking on a traditional survey. In many instances these are ‘low-hanging fruit’ - easy to fix when you know what they are.
One topic that comes up much more frequently than you’d expect with our clients is the music (or lack of it) in the workplace. Recently a large retail client saw a large spike in employees saying that the music in the stores needed fixing.
“Change the music. It’s so moody and depressing and totally not our customer. We have had several complaints from customers and the team”
Looking into the data at who thought that changing the music would improve working life we found that employees who were engaged were 99% more likely to have mentioned that they would like the music choice to be changed than non-engaged employees.
Looking into co-occurrence of topics (ie people who talk about changing the music, what else are they more likely to talk about?) we saw that these employees were more likely to talk about issues with customer service, needing to keep up to date with trends and asking management to listen to them better.
Why was this, an issue which would not have been present on a traditional employee engagement model important to address?
- It was disproportionately impacting engaged employees. Our models suggest it is much more effective to stop disengaging employees than to try and re-engaging disengaged employees. Hence reducing frustrations for those who are currently engaged is a good approach
- It was being linked to a key business metric / outcome - ie customer experience
- It was a change which was easy / cheap to make
- making this change would demonstrate that management was listening in a simple way to a group which was concerned about this.
The change was made and was recognised by a decent number of employees on the next survey.
“Since the last survey, they have changed the music and it creates a better work place for staff and customers”
What is needed to do this
To do this you need several key components that Workometry provides to our clients:
- The text coding is inductive - that is we learn the topics / text categories from the data, not from a standardised or theory-driven model. This is necessary to identify new / unusual topics that might be company-specific
- Context is key. Whilst we code each statement at a very high level of accuracy (due to building question / organization specific inductive models) what is important to decision making is understanding the comment in context to who made it and what else they said. We have algorithms that search for these patterns. It’s relative differences that are important not absolute numbers
- Of course you need to be asking good open questions. We believe that open questions, and their focus on identifying issues that can drive continuous improvement is more important than assessing against a pre-defined model.