Following the onset of The Great Resignation, we’ve seen a disruption in the workforce. No longer are employees taking a wait-and-see approach when it comes to job satisfaction. In fact, according to WTW’s 2022 Global Benefits Attitudes Survey, 44 percent of people currently employed are actively looking for a new job. And the trend is not new. It is deepening. In 2020, 33 percent of workers said they planned to stay in their current roles; in 2019, 47 percent reported planning to stay put.
Successful businesses are built on the hard work of high-quality people. Without them, failure is inevitable. From Richard Branson to Stephen Covey, smart business leaders know that people are an organization’s most valuable asset.
Never has this sentiment been truer than in the manufacturing sector. Of course, many factory processes are now automated but automation is not a catch-all solution and, with the third highest industry rate of staff turnover, the retention of quality workers is one of the biggest challenges facing manufacturers today.
So, what is the solution? The advancements in technology for manufacturing need not be purely centered on automation. Artificial intelligence (AI) and machine learning (ML) offer human-centric solutions that personalize safety, drawing them in as important stakeholders of the business.
AI-driven, worker-centric safety protocols help employees learn more about their movements and help reduce their risk of injury—permanently. They can be sensor-less or use a wearable that incorporates AI/ML to target hazardous movements that could lead to back or shoulder injuries. Such alerts improve awareness to change behavior and reduce the overall risk of injury.
How does this help retention? It starts with understanding the drivers that cause workers to leave their jobs.
Workers want three basic things:
AI safety technologies deliver on each of the three key areas that influence retention. Despite the importance, a large proportion of workers don’t feel their current organization provides them with growth opportunities. The ML algorithms learn from a worker’s behavior patterns and provide personalized recommendations. This actively encourages improvement, showcasing an investment in development, and company commitment to the personal and professional growth and safety of its workers.
Companies that provide effective training have been found to have a 53 percent lower turnover rate. Workers can track progress and analyze their own data, putting them on equal footing with safety leaders and providing them with the tools to have informed conversations to tackle personal safety issues.
Using AI, the individual strengths and achievements of every employee can be highlighted and praised, even in large organizations. Studies indicate only one in every three workers feels regularly recognized for on-the-job achievements. The metrics generated by AI are a reliable way to move the focus away from weaknesses and towards progress, improvement, and strengths.
In recent research from Deloitte, 42 percent of workers attributed burnout as the reason for leaving their job. AI used in different wearable devices is an extremely powerful anti-burnout tool that can identify the risks of injury from movements due to contributing factors such as fatigue, stress, pre-existing injury, or distraction. The safety of any given movement is assessed against a wide range of characteristics, including velocity, jerkiness, and bend angle, leading to a holistic, human-centric approach that sees workers feeling less stressed at work as well in their personal lives.
The data generates true early intervention with workers accessing help before they get injured or report pain. Such programs have been found to have a positive effect on employees, including improved recovery outcomes, increased capacity to remain at work, reduced length of time away from work, and decreased likelihood of further absence due to illness.
Most of all, AI and ML safety technology solutions facilitate the ability for large manufacturing organizations to provide tailored training experiences and development on an industrial scale that otherwise would be impossible. Using worker-centric technology moves away from standardized data and instead prioritizes and adapts to the individual. And it does so without the immense cost of individual coaching. AI can facilitate one-on-one coaching that engages each worker on their own skills and merits, even in organizations with thousands on the factory floor.
Workers who feel valued and are given the opportunity to be actively engaged in their own progress and safety are much less likely to leave, and AI provides the personalized formula on a scalable level. It can provide a cost-effective solution that not only reduces workplace injuries but also helps retain productive people who feel respected and protected.
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