The workforce crisis in manufacturing is at an all-time high. Lack of skilled labor is leading to hiring challenges. Decreased retention rates and the quickly retiring baby boomers are causing workforce instability. Artificial Intelligence is here to help.
This is not your father’s factory floor. Today’s manufacturing workforce is different. It’s rapidly changing. It’s diverse. And it’s dramatically less stable than it used to be.
Today’s workforce challenges stem from the unprecedented levels of dynamism in the areas of skills diversity, reduced tenure, and increased churn. Unlike the stable and predictable workforce of the recent past, today manufacturers must live in the new normal where workers are hard to find, hard to engage, and hard to keep.
Along with the ongoing skills gap crisis and retiring workforce leading to tribal knowledge leaving, today’s workforce is also more dynamic and diverse than previous generations. The 30- year dedicated employees are no longer the norm. The average manufacturing worker tenure is down 17% in the last 5 years and the transient nature of the industrial worker is quickly accelerating. An outgrowth of the COVID pandemic brings forth the Great Resignation, where workers are quitting in record numbers, and worker engagement is down almost 20% in the last 2 years.
The result is that manufacturers are struggling to onboard, guide, and support their frontline workforce so that it can work at acceptable levels of safety, quality, and productivity.
The old way of supporting your workers doesn’t work anymore
Manufacturers are quickly realizing that they can no longer train, guide, and support their workers using the static, “one size fits all” processes from the past. Today’s new workforce is changing in real-time – who shows up, what their skills are, what jobs they need to do, is a constantly moving target. The traditional approaches to training, guidance, and performance support are fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality, and productivity.
They are being forced to rethink everything from hiring, onboarding, training, and retention. The skills gap is widening. The senior workforce is retiring and walking out the door with decades of tribal knowledge that has not been sufficiently captured in a way that can be shared across the entire workforce. Additionally, the new dynamics of hybrid and remote work brought on by the COVID pandemic are placing burdens on traditional training and apprenticeship methods.
Building a Modern, Connected Workforce starts with AI
To deal with this rapidly changing workforce, manufacturers will need a more data-driven, individualized approach to effectively grow and support their workforce.
Many manufacturers are beginning to modernize and connect their workforce with solutions that utilize technology such as mobile and wearable devices, augmented and mixed reality (AR/MR), and artificial intelligence. Connected worker solutions that bring together these technologies are helping to connect a new class of workers and are allowing organizations to proactively and continually deliver the right level of training, guidance, and support.
As workers become more digitally connected, companies have access to a new rich source of activity and job execution data, and with proper tools can gain insights into areas where the largest improvement opportunities exist. The challenge lies in the fact that connected worker data is inherently noisy, creating confusing signals that traditional business intelligence tools can’t interpret.
This is where Artificial Intelligence comes in.
While AI has traditionally been used to automate and replace human jobs, there is greater benefit by using AI to augment human intelligence and make workers more productive. AI algorithms are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse the data, and find correlations and patterns that can be used to identify opportunities for improvement and creates a data-driven environment that supports continuous learning and performance support.
Using AI to Reduce Onboarding Time And Get Workers Productive, Faster
Traditionally, there was a clear separation between training and work execution, requiring onboarding training to encompass everything a worker could possibly do, extending training time and leading to inefficiencies. Today, with the ability to deliver training at the moment of need, onboarding can focus on everything a worker will probably do, significantly reducing onboarding time.
With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If a company can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. This also results in an increase in productivity and worker engagement. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company.
For example, Bio-Chem Fluidics, a leading manufacturer of medical device instrumentation, was able to reduce onboarding time for new employees by up to 80%, while simultaneously achieving a 21% improvement in job productivity across their manufacturing operation. Using AI-based connected worker technology from Augmentir, Bio-Chem not only digitized several of their manufacturing processes, but also gained data-driven insights into areas of improvement within their workforce. Additionally, the time spent monitoring new hires has dramatically reduced from an estimated 50% of a team lead’s time to just 10%.
Deliver Personalized Guidance and Support with AI
With AI and connected worker technology, companies can greatly improve workforce efficiency by converting paper-based processes to digital work instructions and use AI to dynamically personalize those instructions to the needs of your individual workers. This allows companies to provide exactly the right information at the right moment to help workers perform at their personal best.
STRONGARM, a Pennsylvania-based manufacturer of industrial workstations, was able to benefit from this approach. The company recently adopted digital technology to help streamline its assembly workflow with the goal of reducing costs and improving quality and performance across their workforce. When one of their senior and most experienced technicians retired, the company was able to onboard a new technician and leverage AI-based digital work instructions to guide him during the learning curve to get product out the door at 100% quality so that they didn’t miss shipments. Once Augmentir’s AI engine determined that the worker had become proficient, it recommended that the instructions should be adjusted to enable him to complete the job faster while still meeting quality and safety goals. This resulted in a 20% reduction in average build time in their most complex workstations.
Furthermore, workers that require additional support can benefit from AI bots that autonomously deliver a rich set of digital work instructions to that worker so that they can be guided to resolve complex issues independently and complete jobs safely and correctly.
AI Uncovers Previously Hidden Insights into Process Improvement and Worker Productivity
Beyond the direct guidance and support that AI-based solutions can provide to the individual worker, there are also benefits across an entire organization. Using AI-based, data-driven analytics, companies can answer important questions in the areas of process improvement and workforce productivity, including:
- Where should we focus for process improvement?
- What type of training would give us the biggest return?
- Who would benefit the most from targeted training?
- How many hours of productivity opportunity do we have?
- Who should perform this PM?
- What training material needs Improvement?
Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of productivity, quality, and workforce development, setting the stage to address the needs of today’s constantly changing workforce.
Shaping the Future of Manufacturing
Some of the most innovative and forward-thinking manufacturers are realizing that AI is the key to saving the manufacturing world and unlocking worker potential. However, many companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.
This couldn’t be farther from the truth.
AI is already largely embedded in most aspects of our lives. It will play an equally large role in helping augment the manufacturing workforce and the shape next generation of how people work. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth.
As we look ahead, AI will become pervasive in manufacturing, and will be instrumental in shaping the workforce of tomorrow.