The Power of Quality Data Analytics for Self-Insurers

The power of data has been realised in today’s digital world. Data and analytics can boost an organisation’s performance, and many businesses attribute their success to better decision-making through the effective use of analytics. 

So too, in the area of self-insurance, where data analytics allows organisations to gather data from silos and other disparate sources, study it, discover patterns and correlations, and glean vital business insights. 

Benefits of quality data analytics

Self-insurers today are applying data and analytics technology in the area of injury and risk management in order to:

• Optimise decision making
• Improve safety by enhancing injury prevention practices
• Increase productivity
• Mitigate risks
• Reduce cost of replacement workers
• Reduce workers compensation losses
• Maintain compliance
• Safeguard against reputational loss

And if data analytics are lacking?

Executives agree on the importance of data. In the Forbes Insights KPMG 2016 Global CEO Outlook, data and analytics capability ranked the highest of the top five investment priorities for CEOs. Notwithstanding, however, 84%, of the CEOs surveyed, were concerned about the quality of the data on which they were basing their decisions. 

Impact of poor-quality data has been categorised into losses in the four key areas of confidence, opportunity, revenue and reputation.

Self-insured organisations leave themselves exposed if they are basing their injury and workers compensation decisions on unreliable information. And they compound the negative impacts of dodgy data if their analytical tools and methodologies are too cumbersome for agility and insight.

Moving forward

The first step for self-insurers to being able to make smart data-driven decisions, is to capture the right data, and this can only happen through choosing the right injury and risk management platform. Only then, can you ensure data integrity.

Your platform must be able to capture accurate, complete and immediate data, from multiple, disparate locations, and bring it together in the one system. 

At this point, we might consider this amassed data inert, requiring analytic function to bring it to life. So a platform of choice must also provide top-tier analytical and reporting abilities and flexibilities in order to provide organisations with the insights they should be demanding.

Solv: The system of choice

Our clients choose Solv to gain:

• Data integrity: Ensured through in-built validations with mandatory fields, consistency and uniformity
  
• Advanced reporting solution: Embedded into the platform, offering a single view of the most critical injury and claim data across all states
  
• Single or multi-state functionality: Perfect for all self-insurers, whether they operate in one state or more
  
• Easy management of self-insured and non-self-insured policies: Ideal for those organisations with mixed caseloads
  
• Analytical insights: These include:

• Cost breakdown of injuries and claims across your business
• Cost breakdown on injury type and body locations
• Provision of insights from an organisational level, to a regional level, to an individual record level, if required
• Understanding of injury and claim trends across the organisation
• Ability to use insights to forecast potential future costs 
• Access to a suite of pre-built standard system reports, and options to create-your-own reports to meet specific business requirements. 

Preparing for (near) future shock

Widespread adoption of technologies such as automation, artificial intelligence, and the corresponding rise in interconnection and the proliferation of sensors, will see a flood of data delivered to organisations. At that point, it will become even more pressing for all organisations to understand how to hone their data gathering and analysis.