As with anything new, there are always early adopters, slow adopters and in-between adopters, and HR people working with data is no different. So it’s good to see, bearing in mind the dramatic impact using data can have on employee wellbeing and business expenditure, that over two-thirds of employers (69 per cent) are now using data to guide decision-making and measure impact.
Employee health data, although generally not fully utilised to its maximum potential, is phenomenally powerful for a business. It helps target key areas of employee risk, potentially reduce costs and measure performance, let alone pinpoint where healthier behaviours can help prevent issues, rather than focusing purely on cure. It also, importantly, forms the bedrock of a business case for future investment. The hunt for wellbeing budget is a continuing issue so it’s encouraging to see employers accessing a wide range of data sets to help inform their decision-making and guide their strategy.
The ‘what data do you use?’ question was asked in the Aon Benefits & Trends Survey 2019, which surveyed over 200 employers of all sizes, across a broad range of sectors and of which 75 per cent work internationally. All data in this article is from this Survey.
Absence data is the most popular data source to understand and identify risks, with 47 per cent of employers using it. It’s encouraging that they’re also looking to a wide range of other areas to get insights. Employee engagement surveys and EAP utilisation are well used, while medical, income protection, life assurance, critical illness and occupational health data are on the data radar too. One area with surprisingly low utilisation is aggregated health screening data, with only 13 per cent of employers using it. Given the importance of understanding the impact of underlying health behaviours on employee health, I’d expect to see increasing focus on this important data set in the next 12 months. These insights give a DNA of an organisation so HR has information to convert to knowledge and drive strategy.
But before setting out a strategy, it’s important to understand the goal – will the insights be used to improve programmes? Reduce costs? Target absence or presenteeism? Highlight critical issues to the business? Demonstrate success of a particular project? Once the goal is set out, key data streams can be used to help understand the route ahead:
Management information and benefits claims data
This includes data from providers of medical insurance, income protection, life assurance, employee assistance programmes, health screenings and employer’s liability. Claims data and utilisation statistics are largely available and can be an ideal starting point. Insurers have developed standard management information (MI) reporting capabilities and on a standalone basis, with the right interpretation, this can lead to some informed conclusions about prevalent health risks. Areas of the business that disproportionately contribute to a claims experience can be flagged, and positive action taken.
This offers a number of valuable insights including an understanding of the impact of current health strategy and quantifying financial impacts. Assuming the ability to capture data is robust then it can offer a company-wide profile of health risks and absence trends. Where absence analysis becomes even stronger is when it is overlaid against other sets of absence-related data. By comparing absence trends (key health risks, durations etc.) against Occupational Health data or Income Protection claims (or even IP claims notification data) an employer can open up some real insight into the performance of their strategy. For many, the real challenge is the ability to effectively trap robust absence data in the first place. There is a range of absence recording solutions available and there’s potentially a clear value in doing so.
Advanced behavioural data
This provides employers with the greatest understanding of their company’s health profile, beyond claims or absence data, which measure health risks once they’ve already occurred. Behavioural data, on the other hand, highlights underlying human behaviours that drive outcomes. A study conducted by the World Health Organisation in 2010 highlighted the eight common behavioural health risks that drive the 15 most common chronic conditions. These eight risks account for 80 per cent of health claims costs worldwide and are: Poor stress management, Insufficient sleep, Smoking, Excessive alcohol consumption, Poor diet, Physical inactivity, Poor standard of care choice and lack of health screening. They drive claims costs from 15 chronic conditions such as diabetes, coronary artery disease, hypertension, back pain, obesity, cancer and lung disease. The most robust data analysis would aim to understand behaviours and risks at the earliest stage to help guide future strategy. But availability of data or understanding what data sets may be relevant can be a real challenge. Technology plays an important role in accessing new data streams; activity trackers, wearables and mobile health apps can generate significant volumes of data if cultural and employee engagement challenges can be addressed. It’s also possible to get creative in data collection points to evidence health behaviours, such as choices from onsite canteens, take up rates for ‘healthy’ benefits like gym membership and cycle to work and unused annual leave entitlement.
This is where data needs blend with attitudinal research. It’s ideal to go beyond judging engagement from simplistic data like employee website clicks or benefits selection. Far more insightful measures include repeat selections, benefits advocacy or productivity.
In summary, our advice is to use data to analyse the issues that are unique to an individual business, then to ensure that full consideration is given to four key stages of wellbeing: prevention and education, detection and early intervention, access to treatment and long term support.
The mantra ‘prevention is better than cure’ holds very true in employee wellbeing
Interested in HR Analytics? We recommend the Mission Critical HR Analytics Summit 2019.