Goodbye to Absenteeism: Understand the 82 Factors Behind Your Company’s absenteeism
In many companies, absenteeism is still a big and expensive problem. It lowers productivity, creates stress in teams, and hurts overall performance. Even though more employers are focusing on employee wellbeing, it is often still difficult to really understand why people call in sick. A survey by the Chartered Institute of Personnel and Development (CIPD, 2023) found that organizations implementing a continuous improvement and feedback loop approach to their wellbeing programs were 2.58 times more likely to achieve lower sickness absence rates compared to those that did not. This underscores the importance of regularly reflecting on and addressing the root causes of absenteeism as a strategy for reducing sickness absence and improving overall employee wellbeing.
The challenge lies not just in recognizing the symptoms of absenteeism—such as frequent sick leave or reduced employee engagement—but in systematically diagnosing the root causes and acting on it. Tools like the health check (PMO) are instrumental in identifying certain factors related to employee wellbeing. However, while the PMO is valuable for uncovering health-related issues, it often falls short in addressing critical HR policy or organizational factors that may be contributing to absenteeism.
Without a data-driven approach, organizations risk applying broad solutions that don't fully address the real causes of absenteeism. Therefore, resulting in wasted resources, and no reduction in employee absenteeism.
This article aims to inspire you to reflect on whether you truly understand the most important root causes of absenteeism in your organization. Are your decisions based on assumptions, or are they backed by data and a clear understanding of the complex factors at play?
Strategy 1: How Data-Driven Decision-Making tackles Absenteeism
Harnessing the power of data is useful when addressing absenteeism. By collecting and analyzing data from various sources—such as HR records, employee surveys, and productivity metrics—organizations can identify patterns and trends that may not be immediately obvious. For instance, tracking overtime hours in relation to sick leave can reveal if employees are burning out due to excessive workloads. Regularly reviewing this data allows employers to make informed decisions, such as adjusting workloads or implementing wellness programs, ultimately leading to more effective absenteeism management.
From an organizational perspective, there are four key categories you can influence to improve employee wellbeing. It's important to note that there are 82 factors that can impact absenteeism, and we've highlighted just a few examples within each category to inspire you and showcase the wide variety of factors that could be contributing to absenteeism:
Case Example: Predicting Long-Term Absenteeism with Data
One company we worked with had a policy that required employees to meet with the company’s occupational health doctor (arbo-doctor) after three instances of absenteeism. While this policy was well-intentioned, our analysis of their absenteeism data revealed a significant insight: the frequency of absenteeism was a strong predictor of future long-term absenteeism.
Specifically, we found that employees who had taken two short-term leaves within a six-month period were at a much higher risk of transitioning into long-term absenteeism if no intervention occurred. The data showed that waiting until the third instance of absenteeism before initiating a conversation with the arbo-doctor often resulted in missed opportunities for early intervention.
Armed with this insight, we recommended that the company adjust its policy to initiate a conversation with the arbo-doctor after two instances of absenteeism, rather than three. This change allowed for earlier identification of potential long-term absenteeism cases and enabled the company to take preventive measures sooner. As a result, the company saw a noticeable reduction in the number of employees transitioning from short-term to long-term absenteeism, leading to improved overall workforce health and reduced absenteeism costs.
This example underscores the importance of data-driven decision-making. By analyzing the right data, organizations can uncover critical insights that lead to more effective policies and interventions, ultimately improving employee wellbeing and reducing absenteeism.
Understanding the root causes by data driven insights really helps you improve employee wellbeing
By embracing data-driven decision-making and understanding the root causes of absenteeism, you can transform your approach to employee wellbeing. These strategies not only help you address absenteeism more effectively but also foster a healthier, more engaged workforce. Don’t leave your absenteeism management to chance—take the time to reflect on whether your current strategies are based on assumptions or solid data. Implementing these insights today will position your organization for a more productive and resilient future.
Related Insights
