Workplace injury and tech: Predicting and preventing the next employee accident

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  Quntumrun Foresight
• November 23, 2022

Insight summary

Predictive analytics is transforming workplace safety, with firms adopting technology to predict and prevent accidents, enhancing both safety and efficiency. This trend involves using wearables and sensors for real-time data collection and analysis, leading to more informed safety strategies and reduced risk of injury. The shift towards technology-driven safety measures is reshaping how companies approach employee well-being and operational processes.

AI workplace injury context

With workplace accidents imposing significant financial and reputational costs on the industrial and manufacturing sectors, firms are increasingly leveraging predictive analytics. This approach helps in identifying potential risks, enhancing safety measures, and predicting future incidents. Consultancy firm Deloitte reported that in 2022, workplace injuries costed companies in Canada approximately USD $20 billion annually. In the US economy, the costs associated with employee compensation and time off work amounted to around USD $2 billion per week. Beyond the financial implications, workplace injuries also lead to loss of talent and damage to a company's reputation.

The need to address these issues has led businesses to turn to data analytics as a solution. Companies are now actively collecting and analyzing incident reports to pinpoint areas of concern and predict future occurrences. This process involves the use of wearables and sensors to gather data in real time, which is then centralized in a database. This database enables management at various levels to understand incident trends, informing the development of improved safety measures and identifying potential high-risk zones.

The application of predictive analytics in workplace safety represents a shift towards proactive risk management. By utilizing data-driven insights, businesses can not only reduce the frequency and severity of workplace accidents but also optimize their operational processes. As a result, companies not only safeguard their workforce but also enhance their overall productivity and reputation. 

Disruptive impact

Customization of data collection based on specific roles and site-specific factors allows for a more targeted approach to managing risks. For instance, in 2019, NIPO Corporation, a construction company in Japan, equipped their workers with an SOS button. This device enabled workers to immediately alert others in case of injury or illness, facilitating prompt response and potentially reducing the severity of incidents.

Advancements in wearable technology are further enhancing the effectiveness of predictive analytics in the workplace. In 2020, Soter Analytics, an ergonomics technology firm, developed SoterSpine, a wearable device that tracks muscular movements and provides real-time feedback on posture. This kind of technology helps workers make immediate adjustments to their activities, reducing the risk of long-term injuries. 

The economic benefits of predictive analytics in workplace safety are significant. By 2022, an electrical firm reported a reduction in compensation costs by up to 66 percent over two years, thanks to the implementation of predictive analytics. This trend is expected to encourage more companies to adopt similar technologies, leading to a safer and more efficient industrial practices.

Implications of applying advanced analytics to health and safety

Wider implications for applying advanced analytics to workplace health and safety may include:

• Employees being required to wear gadgets such as smartwatches and other wearables to monitor movements, warn of possible accidents, and address problematic workplace habits. 
• Predictive analytics being used to preasses physical accidents and to implement mental health initiatives such as anticipating anxiety-inducing seasons, quarters, or projects.
• Healthcare wearable manufacturers using predictive analytics to offer more sophisticated gadgets, such as chairs that adjust based on real-time employee data. 
• Insurance providers promoting wearable sensors for workers' information tracking. 
• Increasing business opportunities for wearable manufacturers to develop devices for real-time employee tracking.
• Development of industry-specific safety applications using predictive analytics, leading to reduced workplace accidents in high-risk sectors.
• Integration of virtual reality (VR) in safety training programs, enhancing real-world preparedness and response skills in hazardous work environments.

Questions to consider

• How might predictive wearables be invasive to an employee’s everyday movements?
• What are the other benefits of being able to anticipate where and when accidents can occur?