How to use wellbeing data to identify areas of low resilience within your workforce
Rather than taking a blanket or scattergun approach to try and improve employee resilience, employers can focus instead on targeting those pockets of the workforce that have a lower resilience than the norm. The only way to pinpoint these areas, is to gather and effectively analyse wellbeing data from employees.
Gathering the right data
There are a multitude of datapoints that can help you determine the current resilience of your workforce, to determine where best to focus. Some of these datapoints will be existing HR information, such as EAP usage, employee net promoter score (NPS) surveys, absence rates and retention rates. These can begin to show the impacts of low resilience and wellbeing, but they don’t highlight the underlying causes. This is where it’s necessary to gather more specific wellbeing data, to understand which area is causing the most concern and having significant impact on employee wellbeing.
Our recent research on employee wellbeing found that more than half of employees in the UK have less than the recommended three months’ worth of emergency savings – and this was prior to the coronavirus pandemic. Being scarce of financial resilience means it’s no surprise that the same respondents felt that financial worries were their number one concern.
Gathering this kind of wellbeing data often involves asking employees to share personal information and feelings – either qualitative or quantitative – relating to their own mental, physical and/or financial wellbeing. In our experience many employees will be uncomfortable sharing these, even with the reassurance of anonymity and confidentiality from the HR department, meaning that some people don’t share the full extent of issues concerning them and others simply don’t respond. This can lead to significant holes in the base data, resulting in the analysis and solution being flawed.
It can therefore be valuable to use an independent party to hold surveys and focus groups, with experience of how best to collect and analyse employee data to ensure you are collecting the “warts and all” full data set. Questions are set based on similar experiences and can be tailored for your particular workforce. In our experience, employees are assured by the surveyor being separate from their employer and are more comfortable sharing personal details and true feelings about their workplace without fear of ramifications or embarrassment.
Effective analysis
Once your wellbeing data has been gathered, it must be effectively analysed to understand where the pockets of low resilience are, and what the flags or triggers might be. Looking at distinct datapoints in isolation is not helpful – the power comes from layering and analysing data sets over each other.
As an example, if the data shows that women experience lower resilience, is this because they are more likely to be part-time workers, and therefore have lower incomes? Or because they are more likely to be caregivers and have increased stress from this? Or is there a gender bias in the way they are treated at work?
It’s important to avoid correlation rather than causation, and to be able to analyse the data in a way that can control for specific factors so you can find the underlying cause rather than relying on a simplistic view. Again, this is where it can be useful to have independent support to ensure you are avoiding making assumptions and instead use your data to its fullest potential. An experienced data analyser will have experience of where to look and how to best analyse your data. You can also model future scenarios to understand how resilient your workforce is.
We analysed the financial resilience of a client’s employees using a combination of internal and external data sources. Each employees’ financial wellbeing was categorised as red, amber or green based on their disposable income after deducting all living expenses (these were estimated combining company data and external data showing average home expenditure by postcode). Combining financial wellbeing with company sickness data, we saw a higher sickness rate for those that were in the red and amber categories in comparison to those that in the green category.
While on the surface things looked under control for those in the green category, it was a different story when we modelled an unexpected £500 expense on employees. Many moved down to amber or red categories meaning they were then more likely to have increased levels of sickness. While employees were managing their day-to-day ok, they did not have the financial resilience to bounce back from an unexpected expense.
With this information, the organisation was able to look at their internal policies to see what changes could be made to support employees better. They were also able to utilise this information in their next benefit review to see if they could support employees to build up a savings buffer should something unforeseen happen, growing resilience as well as engagement and loyalty within their workforce.
If organisations are aiming to improve employee resilience – whether for altruistic reasons, or to address the underlying causes of poor retention, absence rates or productivity – it’s important to take a considered approach. Analysing specific wellbeing data can help identify the areas of lowest resilience in your organisation, enabling you to have more effective uses of resources when addressing this problem.
This article is provided by LCP.
Financial resilience is just one of the topics that will be discussed during the Employee Wellbeing Congress. Take a look at the full programme, including the smaller group discussion sessions.
