United Kingdom

How to take employee data out of the ‘too difficult’ bucket

Employee health data can be a thorny subject for organisations. While recognised as important to monitor the wellbeing of staff, tailor support and prevent future health risks, obtaining data isn’t always easy. In many cases, a lack of accurate data or disparate data sources can contribute to the issue, at which point extracting and analysing employee datasets far too frequently falls into the ‘too difficult’ bucket.

Without access to these insights, the chance of successfully responding to or, indeed, preventing risks to employee health is minimised. But it’s crucial that employers take steps towards this now. The pandemic has increased the risk of poor health among the UK workforce, from burnout and mental health, to musculoskeletal and low engagement issues.

The Britain’s Healthiest Workplace Survey found that the UK economy lost nearly £92bn due to ill-health related absences and presenteeism at work in 20191. If organisations want to address this, they need to understand what exactly is impacting their workforce.

So, why is health data so hard to access for many organisations? How can employers uncover the insights necessary to inform successful employee health strategies?

The top five problems with employee health data

There are five common issues that contribute to the problem of finding and analysing people data.

1. Gaps in benefits data

Data surrounding employee benefits can provide excellent health insights. Not only can it reveal the number of employees using the rewards on offer, in turn, it can reveal the health problems that workforces are facing.

Realistically though, organisations can’t offer all benefits to all employees, and not all employees will take up these initiatives. This will impact the kinds of insights and the breadth of health data that can be uncovered.

Therefore, while an organisation may offer private medical insurance and see the incidence of mental health support, if PMI isn’t available to all staff, it provides limited views. As well as this, utilising benefits data relies largely on employee uptake and engagement with these initiatives; without high levels of participation, the data that is captured won’t reveal the true state of employee health across the whole organisation – only a snapshot which could give a skewed picture or miss vital information.

2. Accuracy of health data

Obtaining accurate health data that reflects the true nature of employee health can be problematic. Absence data, for example, is one of the most frequently used sources of insight into workforce health and wellbeing. But, when individuals are taking part in flexible and remote work there are increased rates of presenteeism as employees work while sick. This has resulted in employees taking fewer sickness days and the potential underreporting of illnesses.

In fact, in 1995 the average worker lost 7.2 days to sickness absence. Over the years this has fallen, dropping more so with increases in remote and flexible working - down to 3.6 days in 20202 and rising slightly to 4.6 in 20213. The ability of employers to see vital sickness trends within this health data is, as a result, restricted.

3. Leading vs lagging data

Another challenge employers may face is around the stage of health data that organisations have access to. More often, organisations have lagging data - data around illness that reveals when things have already gone wrong - e.g. when employees use private medical insurance or critical illness policies. This data can be used to create risk forecasts which point towards upcoming health trends - perhaps musculoskeletal issues - and pinpoint areas that the organisation should focus on.

Far fewer organisations, however, have leading data that enables them to be more proactive and target problems that could arise in the future. Understanding employee lifestyles could be effective here, yet very few have data around current employee drinking and smoking habits, sleep patterns or stress levels etc, which are major blind spots.

4. Different stakeholders own different areas of health

Commonly, especially among larger organisations, different groups may own different data sets. Employee relations teams may own occupational health and absence management, for example, while health and safety own accident illness stats, and pensions teams keep data around group income protection and life insurance.

With disparate data sources and no processes in place to pull them together, organisations may miss valuable insights.

5. Inaccessible data

In some cases, more sensitive data can be harder to access due to restrictions around it. Information around stress, depression or anxiety, for example, may be deemed as private and, in some cases, GDPR rulings can prevent certain people within the organisation accessing personal information.

This means these topics are often guarded or even side-stepped as shown by the fact that, according to Aon’s Benefits and Trends Survey 2022, just 21% of organisations are conducting stress risk assessments in 20224. Ultimately this means that gaining insights into the factors that cause stress and deteriorating health at work is rarely available.

What should good data look like for a business?

The key to success is having evidence-based data that organisations can use to uncover internal health trends and benchmark against to keep up with industry best practices.

But what are the easiest ways to gain this and remove data from the ‘too difficult’ bucket?

1. Understand the data your organisation needs

Understanding what good data looks like for your organisation requires recognition that, internally, different groups may want different details and outcomes regarding health data. What the exec may want, will likely be different from what HR leaders or managers or practitioners want.

To help, it’s vital that each group is clear on their own objectives and Key Performance Indicators, focusing on points that they deem helpful to their workforce and team.

In doing this, HR and health teams can distil health data into the key areas they feel are vital to track and respond to.

2. Focus on regular employee listening and assessments

During COVID-19, more employers worked to empathise and listen to employee needs. Instead of conducting employee surveys once or twice a year, many employers continue to ‘take the temperature’ of their employees as a whole far more frequently. Employers should continue this trend to ensure they can regularly assess employee health or forthcoming areas of concern.

Surveys like Britain’s Healthiest Workplace, conducted by Vitality in partnership with Aon are an excellent example - not only giving deep insight into lifestyle and health choices of employees, but providing benchmarking data, so that organisations can get actionable insight to create the business case for wellbeing.

3. Engage with teams around you

Engaging with a variety of teams within the organisation can ensure data is more easily uncovered from disparate or harder-to-access sources. Additionally, bring together consultants, providers and occupational health professionals, so they can present their data, providing an understanding of the broader context.

This can open-up discussions around the latest health concerns the employer is experiencing, what it means for the organisation, and how teams can respond.

Complete the Britain’s Healthiest Workplace survey here to get insights on what is working in your organisation to improve health and business outcomes, as well as where the gaps and risks are.








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