By Sharon Harwood-Davis, Head of Corporate Healthcare Pricing
This article explores why leading employers are using claims analytics to identify workforce risks before they impact productivity, absence and benefit costs.
Rising healthcare costs. Increasing sickness absence. Growing demand for mental health support. Pressure to improve productivity and retain talent.
Many employers are facing all these challenges at the same time.
The difficulty isn’t simply understanding what’s happening today. It’s identifying where future risks may emerge and deciding how to intervene before they affect workforce performance, employee wellbeing and business outcomes.
Most organisations already hold valuable information that can help answer these questions. Yet too often, that data sits across different providers, systems and reports, making it difficult to see the bigger picture.
Traditionally, claims analysis within employee benefits focused on a relatively simple objective: understanding what had happened historically. We reviewed private medical insurance (PMI) claims, assessed insurer performance and measured where sustainable renewal costs should sit for the upcoming policy year.
Today, that approach is no longer enough.
As employee benefit costs continue to rise, workforce demographics evolve and employers place greater emphasis on wellbeing, productivity and retention, claims data has become one of the most valuable strategic assets available to organisations.
Importantly, this isn’t just about PMI.
Some of the most powerful insights into future people risk emerge when you combine claims and utilisation data across your entire health and risk benefits programme with internal sickness absence data, creating a more complete picture of workforce health, wellbeing and resilience.
The question employers should be asking is not “What happened last year?” but “What might happen next?”
Why people risk shouldn’t be viewed through a single benefit lens
One of the most common mistakes I see organisations make is analysing each employee benefit in isolation.
PMI claims are reviewed separately from Group Income Protection (GIP). Employee Assistance Programme (EAP) usage is assessed independently from Occupational Health referrals. Health cash plans, virtual GP data and wellbeing platform engagement often sit in entirely separate reports.
The challenge is that people risk doesn’t exist in silos.
Different benefits reveal different workforce risks.
| Data source | Potential insight |
|---|---|
| PMI claims | Identify growing demand for cancer treatment, mental health support or musculoskeletal care |
| EAP usage | Reveal increasing concerns around stress, anxiety, financial wellbeing and family concerns before employees ever seek medical treatment |
| Group Income Protection claims | Insight into conditions most likely to result in long-term absence and workforce disruption |
| Occupational Health referrals | Highlight workplace-related health challenges that may not appear in insurance claims data |
| Sickness absence data | Insights into conditions and short-term absence trends where a robust Day 1 absence recording system is in place and no claims were made |
To understand future workforce risk, you need to examine all available data holistically. Patterns that appear across multiple datasets often provide a far more reliable indication of future risk than any individual metric alone.
How can claims analytics help predict future workforce risk?
Employers who started this journey years ago are now moving beyond benefits reporting and into workforce health forecasting.
Instead of reviewing policies individually, they’re asking broader strategic questions:
- Which health conditions are increasing across our workforce?
- Which employee groups are most vulnerable?
- What risks are likely to affect productivity over the next three to five years?
- Where are we seeing early warning indicators?
- Which interventions are reducing risk most effectively?
- How should future benefits investment be prioritised?
These are not insurance questions. They’re strategic workforce planning questions.
And the answers are often held within your data.
“Employers gaining the greatest value from claims analytics are no longer using data simply to explain the past. They’re using it to identify emerging risks, prioritise investment and make more informed workforce decisions.”
– Sharon Harwood-Davis, Head of Corporate Healthcare Pricing
Why does benefit eligibility matter when assessing people risk?
One of the most important considerations when analysing people risk is recognising that not every employee has access to every benefit.
Many organisations operate tiered benefit structures.
For example, senior leaders may receive comprehensive PMI, health assessments and executive wellbeing support, while other employees may only have access to an Employee Assistance Programme, health cash plan or Occupational Health services.
If your analysis focuses exclusively on PMI claims, it will only reflect a proportion of your workforce. This can lead to inaccurate conclusions.
Effective people risk forecasting should consider:
- Benefit eligibility
- Utilisation patterns
- Workforce demographics
- Engagement levels
Understanding who can access support is just as important as understanding who is using it.
How can you identify early warning signs of future people risk?
One of the greatest strengths of integrated claims analytics is its ability to identify emerging trends before they become significant risks.
For example, organisations might observe:
- Rising EAP usage for stress and anxiety
- Increased mental health consultations through PMI
- Growing Occupational Health referrals
- Higher levels of sickness absence
- An increase in Group Income Protection notifications
Viewed individually, these trends may not appear significant.
Viewed collectively, they can provide a reliable indicator that mental health-related people risk is increasing across the organisation, within specific employee groups or in certain locations.
The objective is not simply to measure activity. It’s to identify the direction of travel.
How can Group Income Protection data predict long-term absence risk?
Group Income Protection remains one of the most underutilised sources of workforce intelligence. Many employers view it solely as a financial protection product. In reality, it can provide valuable insight into the conditions most likely to result in prolonged absence.
When GIP claims analysed alongside PMI, Occupational Health and absence management data, employers can begin to identify:
- Health conditions with the greatest productivity impact
- Areas experiencing prolonged recovery periods
- Rehabilitation success rates
- Early intervention opportunities
- Potential workforce capacity risks
This enables employers to invest in preventative support before employees reach the point of long-term incapacity.
Why you should measure engagement as well as claims
Interestingly, some of the most valuable insights come from analysing what employees are not doing.
Low utilisation can sometimes represent a greater risk than high claims activity. For example:
- Are employees accessing preventative screenings?
- Are at-risk groups engaging with wellbeing resources?
- Are employees using available mental health support?
- Are certain demographic groups underutilising benefits?
Poor engagement may indicate awareness issues, accessibility challenges and/or cultural barriers that could result in higher future health risks. Employers should therefore assess engagement levels alongside traditional claims analysis to build a more complete picture of future risk.
The future of employee benefits strategy: from reporting to prediction
As employee benefits advisers, our role is evolving.
Historically, the focus was on designing, placing and managing benefit programmes. Today, we have an opportunity to help employers unlock a much greater strategic value from the data those benefit programmes generate.
Ultimately, the future of employee benefits analytics is not about understanding who made a claim. It’s about understanding what those claims are telling you about the future health, resilience and performance of your workforce, and using that insight to make better decisions before risk becomes reality.
Key takeaways
- People risk rarely appears in a single dataset.
- The most valuable insights come from connecting multiple sources of workforce data.
- Claims, utilisation and absence data can reveal emerging risks before they become business challenges.
- Benefit eligibility should be factored into any people risk analysis.
- Low engagement may be as important as high claims activity.
- Claims analytics can support workforce planning, not just benefits management.
- Employee benefits advisers can help employers turn workforce data into insight, forecast people risk and make better informed decisions on wellbeing, absence management and benefits investment.
Are emerging people risks hiding in your workforce data?
The warning signs often appear long before absence, productivity loss and rising benefit costs.
Let us help you turn workforce health insight into proactive action.
