Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics - Dikshit, Srishti; Grover, Yashika; Shukla, Pragati; Mishra, Akhil; Sahu, Yash; Kumar, Chandan; Gupta, Muskan (EAI Endorsed Transactions on Internet of Things, 2023)
In today’s fast-paced and competitive corporate landscape, the well-being of employees is paramount for sustained success. This paper explores the transformative potential of predictive analytics in cultivating a healthier, more resilient workforce within high-pressure work environments. The title "Empowering Employee Wellness and Building Resilience in Demanding Work Settings Through Predictive Analytics" encapsulates our objective of harnessing data-driven insights to mitigate the negative effects of high-pressure work settings and foster an environment where employees thrive. Through an in-depth examination of predictive analytics tools and methodologies, this study offers a roadmap for organizations to proactively identify stressors, predict burnout risks, and implement targeted interventions. By collecting and analysing relevant data, employers can tailor support systems, optimize workloads, and implement mindfulness programs that enhance employee well-being. Moreover, organizations can better adapt to change, maintain workforce continuity, and drive productivity by fostering resilience through predictive insights. This research bridges the gap between data science and human resources, offering a holistic approach to employee wellness and resilience-building. By leveraging predictive analytics, companies can create a culture of care where employees feel supported, empowered, and more capable of surviving and thriving in high-pressure work environments.