Connecting the Data Can Change People Risk Outcomes

Organisations access information on workers compensation claims, salary continuance and life insurance claims, absence, employee assistance program usage, engagement, psychosocial hazards, turnover and exit interviews that can provide valuable insights into your people and culture. Other data such as remuneration benchmarks, external industry and regulatory information can provide further context.

The strategic challenge is bringing those different sources together in a way that reveals the connections between them and inform decision making.

In many organisations, people risk data sits across different teams, advisers and providers, each with its own remit, systems and measures of success. The issue is not whether every stakeholder has visibility of everything, it is whether the organisation has a way to connect the most relevant signals, test what they mean in combination and build a clearer view of where risk is emerging.

Case study: When the Obvious Diagnosis Is the Wrong One

A large national retail service provider saw an increase in mental health claims across its life insurance and salary continuance programs. Viewed in isolation, the numbers appeared to point to a growing organisational mental health problem. Mental health was the leading cause of claims, at more than twice the incidence of the next most common condition. But adding additional data told a different story.

The organisation had a high incidence of mental disease claims within its life and salary continuance program, which signalled concern in isolation. Its workers compensation data, however, showed relatively low mental health claim frequency, while the average cost of a mental health workers compensation claim was approximately $17,000, compared with an industry benchmark of more than $25,000. Its premium rate was also consistently below the relevant industry rate. The return-to-work rate on the life insurance program was 67% which indicated people were staying at and returning to work following injury.

When workplace health and safety and internal workforce information were considered, the underlying issue became clearer. Reported psychosocial hazards showed occupational violence as the leading hazard reported, with 128 incidents compared with 45 relating to psychological factors and 38 to job demands. Fifty-nine percent of affected employees were in entry-level, customer-facing roles. The risk was more specific than a general deterioration in workforce mental health. Customer-facing employees were being exposed to occupational violence and aggression.

That distinction changes the response. A broad wellbeing intervention wouldn’t have addressed the true risk. What was actually needed was a targeted approach to de-escalation, occupational violence and frontline risk management. Connecting the data across the organisation provided the opportunity to target the true risk, and ensure valuable resources were directed appropriately.

Case study: When Silos Hide the Bigger Risk

A different organisation experienced the opposite problem. The large financial services business also had workers compensation, life insurance and salary continuance programs, but they were managed by separate teams with separate objectives and limited sharing of data.

On the salary continuance side, claim volumes appeared relatively low and premium performance was good, which signalled to this team that they were performing well. But once the data were connected, more concerning signals emerged. The return-to-work rate was 52 percent, compared with 67 percent in the retail example. At the same time, mental health conditions represented 47.6 percent of workers compensation claims, the average mental health claim cost was approximately $96,000, and workers compensation premiums increased from $1.8 million to $8.3 million over two years.

A deeper review raised an important hypothesis: employees experiencing non-work-related health challenges may not have been accessing the support available through the organisation’s wellbeing and benefits pathways. Instead, some were entering the workers compensation system As the primary avenue to seek support.

Low utilisation in one program can look positive in isolation, however viewed alongside deteriorating performance elsewhere, it may signal that employees are not receiving the right support at the right time. This is the risk of fragmented people data. Organisations can optimise individual programs while overall workforce outcomes deteriorate.

Move From Lagging Indicators to Early Signals

Workers compensation claims and insurance costs remain important measures, but by the time they appear an organisation is often looking at the consequence of a problem rather than its beginning. The aim is not to build a bigger dashboard. It is to ask better questions of the information already available.

If one type of claim is increasing, what is happening elsewhere in the workforce? If utilisation of a support program is unusually low, does that indicate a healthy workforce or a lack of access and engagement? If an organisation appears to have a mental health issue, is the underlying driver workload, leadership capability, occupational violence or something else?

Benchmarking adds another layer. An increase can appear significant internally but look very different when compared with relevant industry experience. Conversely, results that appear acceptable in isolation may be poor compared with peers.

Make People Risk an Enterprise Conversation

People risk intersects with workforce performance, insurance costs, employee experience and organisational risk. Treating each element independently makes it harder to understand both the human and financial consequences of emerging issues.

A more connected approach starts with the governance and operating rhythms needed to bring together the most relevant data, expertise and perspectives across the organisation. HR leaders can ask:

• Are we treating people risk as an enterprise risk rather than a collection of separate programs?
• Are we measuring leading indicators such as absence, turnover, engagement and workload alongside claims?
• Do our leaders have the capability to identify and respond to emerging workforce risks?
• How do we draw a clearer line between people risk and financial outcomes, including premiums and productivity?
• Are we intervening early enough to prevent problems rather than responding after they become claims?

Turning insight into action

Aon’s Human Capital team takes a holistic, data-driven approach to helping organisations understand and manage workforce risk across workers compensation, work health and safety, employee benefits, talent advisory and broking.

That can include bringing together claims and financial performance data, identifying key cost drivers, comparing performance against industry benchmarks and examining the broader workplace factors that may be contributing to risk. Aon can then work with organisations to translate those insights into strategies designed to improve injury prevention, claims management, return-to-work outcomes and overall program performance.

The data may already exist. The better decision comes from understanding what it is telling you.