How Data Analytics is Turning Around Employee Wellness Programs

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As a result of the global pandemic, employee wellness has now taken center stage for companies. Businesses are realizing that poor physical and mental health among their employees can have real monetary consequences. In the US alone, poor employee health costs businesses up to $530 billion annually as a result of low employee productivity and higher payouts for employee health benefits.

The pandemic has also exacerbated mental health issues, leading to employee burnout and low morale. One report states that 30% of short-term and long-term disability claims in Canada were due to mental health issues.

Well-structured employee wellness programs can help companies take a proactive approach and save on costs in the long-term. They can improve productivity, boost morale and significantly reduce attrition. Data analytics can hold the key to developing personalized and effective employee wellness programs.

In the US alone, poor employee health costs businesses up to $530 billion annually as a result of low employee productivity and higher payouts for employee health benefits.

Here’s how employee wellness solutions are integrating data science algorithms to improve outcomes in your organization.

Analyzing data can help you understand current employee health trends 

Before devising a new employee wellness program, it’s important to understand where most of your employee health costs are currently going. Data science algorithms can help identify commonly recurring health issues and the most prevalent health risks among employees.

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