In the employee feedback space there's a lot of hype about linkage for good reason. Linking the data from your people surveys to broader business outcomes can be incredibly powerful. It’s an effective way to demonstrate to leaders that looking after and caring about your people does deliver tangible business benefits, like making your customers happier.
Linkage connects business outcomes with employee feedback
Linkage is when the rubber hits the road with employee feedback. It makes real connections between your business objectives and employees’ experience in your organization. This is what most leaders, executives, boards and shareholders care about. For example, by demonstrating a link between training perceptions and sales performance in one part of an organization, a case can readily be made to invest in training across the entire organization.
Previously it was incredibly expensive to apply statistical techniques on large datasets to make these linkages. Now we have tools that can enable people in almost every company to do this if they set their mind to it.
Some of the classic things that we’re seeing clients link to employee feedback are churn and retention rates. This allows organizations to look at the type of experiences or structural things that lead people to leave their organization. We have consistently seen good linkages in this area.
We have also have seen strong connections between engagement levels and customer satisfaction, particularly in call centres or other parts of an organization where there is a direct relationship with customers. If people are engaged and motivated in a call centre that is typically reflected in a better customer experience.
Be realistic when you first make linkages
While linking employee feedback to outcomes can be powerful it can also be incredibly complex, particularly if an outcome has multiple inputs or causal factors. If there are lots of hidden variables that we’re not able to accurately measure it can be difficult to show an association between the people side of things and the outcome. That’s why it’s important to be realistic and understand that some things are potentially outside the sphere of what you can measure or model.
In other situations you may be able to take some of the causal factors into account in your model. For example:
If you’re looking at growth in a particular country, you can control for how long you’ve been in that market.
When you’re looking at sales growth that is enabled by training you may need to take into account the size of people’s territories.
This can make your model more robust and help you get a better return from your analysis.
Examine the usefulness of the information in your linkage
When choosing your variables it’s also worth considering whether the linkages you’re making will provide valuable information that your organization can use. One organization we worked with was looking for linkages between the wellbeing of their people and workplace performance / retention. They added a variable that considered the level of social support that someone had outside of the organization.
Interestingly, the analysis found that people with strong social support were more likely to leave the business. But this linkage didn’t actually help the organization because they couldn’t reduce the amount of social support a person had outside of the business (and wouldn’t choose to do so even if they could).
My best tip when it comes to linkage analysis
The best tip I can give when it comes to linkage analysis is to start with something small. Start somewhere you have confidence that there’s a connection and you have a reasonable level of control over the inputs going into the system. This will give you the best chance of demonstrating the connection. Great places to start are call centre engagement and customer satisfaction, engagement levels and employee retention, or training and sales performance as they often have clear linkages.
Once you’ve been able to demonstrate a successful link between a people practice and a business outcome you can then progress to adding new variables or making more complex linkages. The results will help you show your leadership the benefits of looking after your people, and can inform your people strategy into the future.
How to get started with simple linkage
Although we can very easily get quite sophisticated in our linkage analyses (we often use machine learning techniques such as Random Forests and Support Vector Machines for example) this isn’t always necessary. We’ve often seen our customers identify key linkages by simply getting the right data together and uploaded into their feedback dashboards. This allows some straight-forward but powerfully simple linkages to be seen quite dramatically.
One of the most common examples of this is when an organization simply tracks which employees have exited the organization over time and then uploads this as a simple flag in previous feedback surveys. This can clearly show the areas in which exiting employees were having their most negative experiences prior to leaving - which is a quite powerful guide to where you might direct your attention to address future retention.
In the screenshot below you can see a simple heatmap. This shows how employees who have subsequently exited the organization were having negative experiences associated with Innovation.
This linkage clearly shows that exited employees here had much lower scores particularly in regards to how they felt innovative ideas we acted on.
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