According to a 2021 study by Deloitte, 77% of surveyed manufacturers say they will have ongoing difficulties in recruiting and retaining employees for the foreseeable future. To make this matter worse, the average tenure rate in manufacturing has fallen off a cliff. Simply put, for today’s manufacturing companies, it has become difficult, if not impossible to effectively hire, train and retain the workers necessary to meet production demands. Industry leaders must consider adapting their hiring, onboarding and training processes to support a more flexible, more dynamic future workforce in manufacturing.
Research by Brandon Hall Group found that companies with an efficient onboarding process increase employee retention by 82% and productivity by 70%. With the cost of replacing an employee ranging between 90% and 200% of their annual salary, implementing processes that lead to reduced onboarding times, improved job satisfaction and improved retention are a worthwhile investment for industrial companies.
Given these conditions, successful organizations must adopt new strategies as they seek to achieve their production goals in today’s era of workforce unpredictability. Organizations that incorporate modern, digital learning technologies and artificial intelligence (AI) in their workforce training and management strategy can experience upward trends in recruitment, job satisfaction and retention for years to come.
Barriers to Recruiting and Retaining Top Talent in Manufacturing
The traditional barriers to recruitment and retention are largely centered around the skills gap amplified by the “Great Retirement” trend: Nearly 30 million skilled and qualified industry veterans of the Baby Boomer generation retired in the later part of 2020. Couple this with the limited talent pool and workforce unpredictability due to the more recent Great Resignation and the result is a massive job shortage in manufacturing that is only projected to get worse.
Although it has become increasingly challenging to recruit and retain top talent, AI-based personalization in the areas of training and performance support can help employers overcome the lack of a skilled, qualified manufacturing workforce.
When companies can’t find skilled resources to hire, often their only option is hiring less skilled workers, who require more training and onboarding to become proficient. Work instructions that are not only digitized but also personalized to each worker based on their skills, training and actual job performance can help these novice or less-skilled workers become proficient more quickly – effectively upskilling each worker at their moment of need. The benefits of individualized performance support and guidance go well beyond increased proficiency and onboarding speeds to include: heightened adherence to compliance, safety and quality protocols, reductions in defects and waste, and improvement in training effectiveness centered around on-the-job training.
The existing skills gap, the ongoing labor shortage issue, and the challenge of decreased tenure rates amount to a highly unpredictable and transient workforce making the need for a flexible workforce more critical than ever.
What’s Needed to Enable the Flexible Workforce of the Future
A critical requirement to make this a reality is digitally connecting the workforce and providing access to data about the work being done: more specifically, real-time workforce intelligence that delivers actionable insights that can be used to individualize the on-the-job guidance and support that workers receive. This effectively closes the loop between training and on-the-job support, and this is only possible with AI.
AI-based analytics offer insights into workforce performance, and can be used to drive individualized training and job support for the workers that need it most, empowering upper management to make informed workforce development and training decisions, and giving workers the support and help they need to perform at their best. Much in the same way that AI is being used behind the scenes to individualize and personalize our online web and shopping experiences, AI can also be used to individualize and personalize job experiences for one of the most challenged workforces today.
With the advent of AI-based connected worker tools, companies can now gather the high granularity data that is required to support continuous improvement initiatives. AI enables accurate insights into the opportunities across an organization’s workforce and work processes by automatically filtering out the noise from the “true” performance data.
With designed for purpose AI, industry professionals can benefit from workforce and work process intelligence without requiring data scientists. Workforce intelligence helps employers understand their workforce at an individual level, in real-time, so that they can intelligently target reskilling and upskilling investments to close skills gaps. Work process intelligence helps organizations understand which work processes have the largest capturable productivity opportunities, enabling continuous improvement teams to focus their efforts and do more with less.
The Meaning and Importance of Democratizing Manufacturing
With learning technologies supporting digital work instructions and delivering AI-based personalized guidance and support, today’s diverse and variable manufacturing workforce can now be empowered to assist with tasks that had historically been outside of their skill set or experience. Autonomous maintenance (AM) is a great example of this level of democratization; this is an approach to maintenance that involves giving machine operators responsibility for basic maintenance tasks, which allows dedicated maintenance teams to focus on more complex maintenance tasks. This strategy is a pillar of total productive maintenance (TPM), an approach designed to optimize equipment performance and a foundational aspect of any lean manufacturing environment.
AM gives operators more control over cleaning, lubricating and inspecting their own equipment, and helps to proactively identify equipment issues before issues arise. Successful AM requires that manufacturers provide their operators with the appropriate digital tools and knowledge to perform these tasks independently. This involves digitizing standard operating procedures (SOPs) for the maintenance tasks as well a providing operators with easy access to training and knowledge base of information. AI can ensure that each worker receives the personalized guidance and support that they need to perform this work safely, correctly, and at their peak productivity.
AI will transform training and performance support for the industrial workforce for years to come. Connected solutions that are rooted in an AI foundation are uniquely able to support continuous improvement and lean initiatives in the workplace, delivering value that increases over time. Just as AI is improving our personal lives on an everyday basis, it will do the same for the future industrial workforce by helping workers perform their jobs at peak efficiency, leading to a strengthened, more confident and flexible workforce.
