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Today’s dynamic and changing manufacturing workforce needs continuous learning and performance support to effectively sustain and deliver effective on-the-job performance.

Every day we hear about the growing manufacturing “Skills Gap” associated with the industrial frontline workforce. The story is that 30% of workers are retiring in the near future and they are taking their 30+ years of tribal knowledge with them, creating the need to quickly upskill their more junior replacements. In an attempt to solve the knowledge gap issues, an entire generation of companies set out to build “Connected Worker” software applications, however, they all relied on the existing training, guidance, and support processes – the only true difference with this approach has been the creation of technology that takes your paper procedures and puts them on glass.

Along with 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. 

This new manufacturing workforce is changing in real-time – who shows up, what their skills are, and what jobs they need to do is a constantly moving target. The traditional “one size fits all” approach to training, guidance, and performance support is fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality and productivity. 

Digitizing work instructions is a great start to helping close the manufacturing skills gap, but alone, it won’t help completely solve the problem. We must go a step further to overcome the lack of a skilled and qualified manufacturing workforce. 

Enter the 2nd generation of Connected Worker software, one based on a data-driven, AI-supported approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities. 

These 2nd generation connected worker solutions are designed to capture highly granular data streaming from connected frontline workers. These platforms are built from the ground up on an artificial intelligence (AI) foundation. AI algorithms are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse 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.

This approach aligns perfectly with the dynamic, changing nature of today’s workforce, and is ideally suited to support their 5 Moments of Need, a framework for gaining and sustaining effective on-the-job performance.

For example, Augmentir’s AI-powered connected worker platform leverages anonymized data from millions of job executions to significantly improve and expand its ability to automatically deliver in-app AI insights in the areas of productivity, safety, and workforce development. These insights are central to Augmentir’s True Proficiency™ scoring, which helps to objectively baseline each of your team members for their level of proficiency at every task so organizations can optimize productivity and throughput, intelligently schedule based on proficiency and skill-levels, and personalize the level of guidance and support to meet the needs of each member of the workforce.

This provides significant benefits to Augmentir customers, who leverage Augmentir’s AI in conjunction with the platform’s digital workflow and remote collaboration capabilities, allowing them to deliver continuous improvement initiatives centered on workforce development. These customers are able to utilize the insights generated from Augmentir’s AI to deliver objective performance reviews, automatically identify where productivity is lagging (or has the potential to lag), increase worker engagement, and deliver highly personalized job instructions based on worker proficiency.

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, identifying and closing skills gap in real-time and significantly reducing manufacturing onboarding times. In one particular case, Bio-Chem Fluidics 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.

As workers become more connected, companies have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce.

Augmentir, a data-driven, AI-powered Connected Worker solution ensures that your frontline workers can go the extra mile every day by providing training, guidance, and support through the combination of digital work instructions, remote collaboration, and advanced on-the-job training.

In 2009, the Extra Mile America Foundation, a foundation promoting action and empowering positive change, first celebrated the “Extra Mile Day”.  Fast forward to 2014 and 527 US cities declared November 1st as the official “Extra Mile Day”. This day is designated to living life to your full potential, having a positive influence, and always striving to make the world a better place. At Augmentir, we believe in positive change, living to your full potential, and going the extra mile every day. In 2017, our founders decided to continue their journey of creating some of the most important software technology revolutions in manufacturing (Wonderware (1987), Lighthammer (1997), and ThingWorx (2008) by focusing on the most important asset, the frontline workers.

We recognize that today’s industrial workforce is different, and the old way of supporting workers just doesn’t work anymore. The static “one size fits all” approach used in the past, no longer applies to this generation of workers.

Augmentir, is a data-driven, AI-powered Connected Worker solution that ensures that frontline workers can go the extra mile every day by providing training, guidance, and support through the combination of digital work instructions, remote collaboration, and advanced on-the-job training.  

As your workers become more connected, companies have access to a new rich source of activity, execution, and tribal data, and with proper AI tools they can gain real-time insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce.

When it comes to our frontline workers, let’s enable them to go the extra mile, not just on November 1st, but every day, by empowering them with the only AI-powered Connected Worker solution.

You may have noticed that our website and brand look a little different. Augmentir has a new look, but under the hood, its the same powerful AI that is helping to transform the industrial workforce of the future.

You may have noticed that our website and brand look a little different. Well, that’s because behind the scenes for the past few months, we’ve been under construction (no pun intended).

Augmentir was founded in 2017 with the vision to use AI to empower the industrial frontline workforce to perform at their best. This was a continuation of our rich history – our founding team has been at the forefront of three of the most important of these software technology revolutions in manufacturing over the past three decades – Wonderware Software in 1987, Lighthammer in 1997, and ThingWorx in 2008.

A lot has changed since then. The world we live in today is not the same as it was 4 years ago. And in the last two years, the COVID-19 pandemic has altered the stability of the workforce and drastically magnified some of the industry’s top workforce challenges, which stem from the unprecedented levels of dynamism in the areas of skills diversity, reduced tenure, and increased churn from the “Great Resignation”. Unlike the stable and predictable workforce of the recent past, today companies have to live in the new normal where workers are hard to find, hard to engage, and hard to keep.

These top challenges of today have only reinforced the need for an AI-powered, data-driven approach to empowering frontline workers.

This data-driven era we’re entering into is one of continuous learning and development with tools like remote collaboration and digitized work processes truly integrating frontline workers into the fabric of the business from a collaboration standpoint whereas they may have been overlooked before.

Augmentir’s AI-powered connected worker platform provides the tools to not only survive in this new normal but to thrive.

You can’t build a truly modern, connected workforce without AI

The term “connected worker” has become a recent buzzword in the manufacturing world, and is now considered a tool that the new generation of workers expect to work with. But true connected work means using AI to allow frontline workers to have access to internal and external resources that are appropriate for when and how they need them.

Augmentir isn’t your typical connected worker platform. Our platform was built from the ground up on an AI foundation. AI algorithms are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse data and find correlations and patterns that can be used to identify opportunities for improvement and create a data-driven environment that supports continuous learning and performance support. Our connected worker platform utilizes AI to help train, guide, and support today’s frontline workers in a dynamic workforce by combining digital work instructions, remote collaboration, continuous development and advanced on-the-job training capabilities.

This approach aligns perfectly with the dynamic, changing nature of today’s workforce, and is ideally suited to achieve and sustain effective on-the-job performance.

As the world’s only AI-powered connected worker platform, we decided it was time to refresh our brand identity to accentuate our strongest feature and the thing that makes Augmentir unique – AI. We’re still the same AI-first connected worker platform that you know – just with a new look.

Augmentir CEO Russ Fadel had the opportunity to be interviewed recently by Ann Wyatt, Industry 4.0 and IIoT Enthusiast, for the OnRamp Manufacturing Conference.

Earlier this month, Russ Fadel had the opportunity to be interviewed by Ann Wyatt, Industry 4.0 and IIoT Enthusiast, for the OnRamp Manufacturing Conference. OnRamp Manufacturing is the leading conference for manufacturing innovation that brings together the manufacturing industry’s leading corporations, investors, and startups. The conference highlighted innovations disrupting the manufacturing industry, the leaders making such innovations possible, and how new technologies and business models will reinvent the industry. In this exciting interview, Ann and Russ discussed some of the top challenges that today’s manufacturers face, and how technology such as AI and connected worker solutions that recognize the variability in today’s workforce are empowering workers by giving them tools and resources that will set them up for success. 

The following is a recap of some of the highlights of the discussion.

The great resignation is upon us now

The consistent story of the manufacturing workforce is that there is an aging workforce and 30-40% of that workforce will leave within the next 5 years, taking valuable, hard to capture tribal knowledge with them. Many manufacturers were under the misconception that the remitting workforce would pass down their knowledge to the next generation as they did before. However, this was a big misconception. Even prior to Covid, the dynamics of the workforce themself have changed. In the last 5 years, the tenure of manufacturing workers is down to 17% and that decrease escalated even more as a result of the pandemic.

The stability of the workforce has decreased in the past 8 years. Old work processes were designed during a more stable time and unfortunately aren’t applicable for this generation of workers. Today’s workers are in the factory less frequently, don’t stay as long, and due to Covid, may be out for short periods of time, resulting in the need for a more dynamic workforce. To deal with this rapidly changing workforce, manufacturers will need a more data-driven approach powered by AI to empower their workforce.

A highly effective, cross functioning workforce

Over the years, the manufacturing industry has done a really good job of connecting machines into the fabric of the business and giving operators the necessary data to help run those machines better. Our frontline workers, the last piece of connectivity, are the least connected set of workers in the company. Frontline workers should be fully integrated into the fabric of the business from a collaboration standpoint so that they can access the data they need as well. Secondly, when they are working, it needs to be understood what workers are doing well and what they are struggling with, so we can match people with the tasks that they already excel at.

Top trends and key challenges in today’s workforce

At the highest level, everyone is talking about the disruption of the mobile supply chain. The role of the manufacturer is to put supply into the supply chain and to safely build products at acceptable quality and productivity levels, matching today’s workforce with today’s task load. 

The new dynamics of the workforce (lots of turnover, shorter tenure, people leaving abruptly) are at odds with what manufacturers are trying to do, which is to be a stable source of supply to the global supply network. Technology today, specifically AI, lets us understand at a data-driven level and in real time how workers can perform at their individual best, based on their training experience and raw ability for a specific task.

How Hybrid Work is impacting the manufacturing workforce

With Covid came an immediate need for remote presence, but the real issue is the idea that a subject matter expert needed to be on site for support. This way of working is now a thing of the past. When we think about having frontline workers fully connected to the organization, at any moment in time, they should have direct access to the tools and resources that would help them do their job better. Connected work in the future means using AI to allow frontline workers to have access to internal and external resources that are appropriate for them at their fingertips.

Another interesting statistic resulting from Covid is that employee engagement is down almost 20% from pre-Covid times. Manufacturers are always concerned about employee engagement, particularly with certain jobs that might be repetitive. AI is extremely helpful in measuring signals of engagement but also provides tools to the organization to increase the level of engagement of frontline workers. One thing that causes a reduction in engagement is when a worker feels like they can’t perform a job so they become frustrated. 

Using AI to give frontline workers the tools and information they need when they need it is one way to help increase engagement. The other way is to let them feel connected to the actual importance of their work.

Hiring, Training & Reskilling

The new workforce dynamics and the nature of hybrid work are also now forcing manufacturers to re-think employee onboarding and training.

The historic methods of onboarding and training taught workers everything they could “possibly” do which resulted in overtraining. The data-driven era we’re entering into is one of continuous learning and development powered by AI. Training shifts from the things frontline workers are possibly going to do to what they are probably going to do. This results in reduced training times, continuous learning and development, and the ability to upskill at any point as needed. Learning is always available, training content is available to the worker on the shop floor at the time of need. Reducing the initial onboarding training and allowing training to occur at the moment of need, coupled with AI for scoring, provides insights into the most effective training modules as well as what needs to improve based on demonstrated execution.

Transforming Today’s Workforce with AI & Connected Worker Tools

One challenge with connected worker data is that it’s inherently noisy. In many cases, up to 37% of the signals that come back are not representative of what is actually happening. Fortunately, AI excels at recognizing patterns in noisy data, so we can use that to focus companies on the work processes that have the most opportunity, allowing organizations to understand their actual proficiency at any procedure or job. This helps them understand current workforce skills, what areas need to be connected or improved, and where they should invest if they want to get the largest return, with AI being the driving technology that unlocks those signals in noisy data.

AI is largely embedded in most aspects of our lives and it will play an equally large role in helping the connected workforce progress and become part of the 21st-century solution and the next generation of how people work. Adopting these methodologies early on will make the overall digital transformation process a lot easier for manufacturers.

AI-powered technology may be the missing puzzle piece for today’s workforce crisis.

AI-powered technology may be the missing puzzle piece for today’s workforce crisis in manufacturing.

Is it just us or does recruiting, training, and retaining top talent today feel a lot like searching for that one elusive puzzle piece? The seismic shift in the workforce is forcing us to get creative and be adaptable like never before.  It’s a new generation and if we want to be competitive in hiring in this ultra-competitive environment, we need to re-access how we train, develop, and retain talent, embrace the variable nature of the labor market, and meet workers where they are. 

We can no longer try to force-fit the old model of staffing and training into a space that looks drastically different. It’s not just about a labor shortage or the supply chain challenges created by the pandemic. Workers themselves are changing. What they want from work, and how they want to work.

The solution to this head-scratching puzzle? AI-based technology. Digital work instructions and individualized training and on-the-job support can improve productivity, reliability, independence, and safety for every worker. It offers flexibility in scheduling for operations managers. It reduces downtime. All of which contribute to a more efficient – and profitable – operation.

Sound too good to be true? Brace yourselves. It’s not. Here are three ways that AI-powered technology can help.

1. Moving onboarding and training closer to the point of work

Imagine if we could train and develop someone in the context of doing their work, leading to increased engagement and allowing organizations to retain top talent. Furthermore, we could see an increase in productivity as they constantly evolve their learnings.

AI is allowing companies to understand a worker’s skillset and provides the ability for personalized digital work instructions to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets and get those individuals productive faster.

2. Give support at the moment of need

Are you a people watcher? We are. Ever take notice of who is on the factory floor? Last time I checked, we got the “newbies” and “veterans”. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach to troubleshooting and performance support.

Enter AI.

Give workers the support and guidance they need, at the moment of need, whether it’s immediate access to a digital troubleshooting guide, or connecting virtually with a subject matter expert.  Delivering personalized work procedures for every worker allows for continuous learning and growth.

3. Improve engagement and retention

Workers that are connected and empowered with digital technology can discover and nurture diverse skills based on their unique competencies and experience. They can earn greater responsibility and independence. This increases confidence and job satisfaction. Which in turn can improve employee retention and slow the revolving door of continual recruiting and training. 

The aftermath?

Workers are likely to stay and want to grow in the company when they feel included. Shortly, workers begin walking with poise and a “can-do” attitude to their next job task.

 

What else is possible with AI-powered connected worker technology?

AI-based technology is ideal for training workers in this variable environment. AI-based systems individualize information about workers based on previous training and data-driven performance insights and augments their capabilities. It offers step-by-step guidance at the moment of need for regularly scheduled maintenance as well as troubleshooting. It helps managers learn about workers’ existing skills and build a rationale for specific roles, resources, and certification support and then make clear recommendations based on demands.

Technology should fit into your business as simply as sliding that last puzzle piece into place. Workers are the heart of your business, and you should adapt technology to fit your business, not the other way around.

Technology should fit into your business as simply as sliding that last puzzle piece into place. That includes how you train your workers. But no two workers are exactly alike. Each will learn and approach problems differently. So why not use the technology that recognizes and adapts to those differences to your advantage?

 

To learn more about how Augmentir can help you embrace this opportunity, contact us for a personalized demo.

Learn about the best practices for optimal asset maintenance performance and how to track your assets to ensure that everything is in working condition.

Onboarding and training are essential components of integrating new employees into a manufacturing environment. Research by Brandon Hall Group found that organizations with a strong onboarding process improve new hire retention by 82% and productivity by over 70%. Additionally, research from NAM and The Manufacturing Institute has found that manufacturing organizations invest an average of 51.4 hours per employee in training and are increasing overall investment in training by an average of 60% in response to the growing skilled labor crisis.

onboarding vs training in manufacturing

Onboarding and training are two key components of a skilled workforce that, while similar, serve different purposes and cover distinct aspects of the employment process.

Both processes are crucial, as onboarding ensures that employees understand the organization’s broader context, and training ensures that they have the expertise to contribute to the manufacturing processes and meet quality and safety standards.

A successful combination of effective onboarding and comprehensive training can lead to more engaged, skilled, and productive employees in the manufacturing industry. Unfortunately, according to Gallup, only 29% of new hires say they feel fully prepared and supported to excel in their role after their onboarding experience.

Read below to learn more about the differences between onboarding and training in manufacturing, why they are both critical to manufacturing success, the benefits of improving them, and how continuous learning strategies coupled with connected worker solutions can improve both and deliver impressive results.

Breakdown of Onboarding and Training Differences

Onboarding in manufacturing is about orienting new hires to the company as a whole, while training is about equipping them with the specific skills and knowledge needed to perform their job functions effectively. Below a breakdown of the differences between onboarding and training in a manufacturing setting:

Onboarding

  • Purpose: Onboarding integrates a new employee into the organization and its culture. It aims to familiarize employees with the company, its policies and procedures, and their roles within the organization.
  • Focus: Onboarding focuses on introducing employees to the broader aspects of the company, such as its mission, values, and culture, as well as administrative and safety procedures.
  • Duration: Onboarding is typically a short-term process, often lasting a few days, but could extend to a few months in certain manufacturing environments.
  • Components: It may include activities like completing paperwork, understanding company policies, meeting the team, plant/site safety, and familiarizing a new hire with the physical workplace.

Training

  • Purpose: Training in manufacturing is a more specific and in-depth process that imparts the knowledge, skills, and competencies necessary to perform the job effectively. It is task-oriented and aimed at ensuring that employees can carry out their roles proficiently.
  • Focus: Training focuses on the technical aspects of the job, safety protocols, equipment operation, quality standards, and other job-specific skills.
  • Duration: Training is an ongoing process and may vary in duration depending on the complexity of the role and the employee’s experience level.
  • Components: Training tends to include hands-on instruction, demonstrations, practice exercises, and assessments to ensure that employees gain the necessary skills and knowledge.
Pro Tip

Both initial onboarding and ongoing training can be implemented with mobile learning solutions that leverage connected worker technology and AI to provide workers with bite-sized, on-demand training modules that they can access on smartphones or tablets. These modules can be developed with customized learning paths that are focused on the type of tasks and work employees are doing on the factory floor.

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Why are training and onboarding important to manufacturing success

Onboarding and training are crucial to manufacturing success for several reasons including safety, compliance, quality, and more. A well-trained manufacturing workforce that has a deep understanding of company policies, its mission, and overall values drives successful initiatives by producing quality products, complying with both industry-wide and company-specific standards, and meeting production goals in a manner that is both safe and efficient.

The manufacturing industry is subject to numerous regulations related to safety, environmental practices, and product quality. Proper training ensures that employees are aware of and adhere to these regulations, reducing the risk of compliance violations and a well-structured onboarding program leads to lower turnover rates and a more effective and cohesive workforce, ultimately contributing to manufacturing success.

In summary, these two tools are essential in manufacturing for setting the stage for employee success and overall organizational success. Onboarding aligns new employees with the company’s culture, policies, and expectations, enhances their safety awareness, and fosters engagement and productivity, while training plays a pivotal role in contributing to manufacturing success by equipping employees with the knowledge, skills, and competencies necessary to perform their roles effectively.

What are the benefits of improving training and onboarding in manufacturing

Improving manufacturing employee onboarding and training offers several advantages, benefiting both the company and its employees. Comprehensive onboarding makes new hires feel connected to the company’s culture and values, while ongoing training can offer growth and development opportunities, leading to increased employee engagement and job satisfaction.

Companies with a skilled, well-trained workforce are more competitive in the marketplace, as they can produce higher-quality products at a lower cost and adapt to industry changes more effectively.

Training and development opportunities are often cited as a key factor in employee satisfaction. When employees feel that their skills are being enhanced and their careers are advancing, they are more likely to be satisfied with their jobs.

How continuous learning and connected worker solutions improve training and onboarding in manufacturing

Continuous learning and connected worker solutions can significantly enhance training and onboarding in manufacturing by providing more dynamic, effective, and adaptable approaches.

By incorporating continuous learning and connected worker solutions into the these processes, manufacturing companies can create more efficient, engaging, and rewarding experiences for employees. This not only accelerates the integration of new employees but also supports ongoing skill development and knowledge retention once on the job, ultimately improving productivity and the overall success of the organization.

connected worker as part of connected enterprise

Augmentir’s AI-based connected worker solution is being leveraged by manufacturing leaders to deliver continuous learning and development tools to optimize onboarding training for a rapidly changing and diverse workforce. Our innovative, smart connected worker suite is transforming how manufacturing organizations hire, onboard, train, and deliver on-the-job guidance and support.

 

digital skills management in a paperless factory

Schedule a live demo today to learn how our smart, connected worker solutions, AI-driven insights, and digital skills management are optimizing training and onboarding programs, tracking individual and team progress, and delivering targeted training and upskilling.

 

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After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:

  • The use of AI to Improve Quality, Reduce Defects, and Increase Profits
  • Developing a Digital Twin to Optimize Plant Operations
  • Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
  • Designing  Products Enabled by Additive and Hybrid Manufacturing Techniques
  • Exploring the Use of AI in Industrial Attacks and Defense

Using AI to Unlock the True Potential of Today’s Modern, Connected Workforce

Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning. 

The Misunderstood Fear of AI

Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, 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.  

As we’ve seen with our customers, this couldn’t be farther from the truth. 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. 

Understanding Today’s Struggles Within Manufacturing

Manufacturing workforce challenges

The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance. 

Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations. 

Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.

Leveraging AI to Help Build and Grow a Top Performing Workforce

Build and grow a top performing manufacturing workforce

AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time. 

The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow. 

With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.

AI in Manufacturing will solve many of the challenges that we are seeing. 

Learning & Development and the 5 Moments of Need

The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.  

According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of: 

  • When people are learning how to do something for the first time (New).
  • When people are expanding the breadth and depth of what they have learned (More).
  • When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
  • When problems arise, or things break or don’t work the way they were intended (Solve).
  • When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).

The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.

Looking Ahead

We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.

Recently, Augmentir completed a rigorous qualification audit as part of a Tier 1 Pharmaceutical Manufacturing company’s Good Manufacturing Practice (GMP), and we are pleased to announce that our product successfully passed the audit.

A recent article published by The Washington Post shows some shocking numbers on the amount of Americans leaving their jobs over the past year. It’s no surprise that hotel and restaurant workers are resigning in high numbers due to the pandemic, but what is surprising is the fact that the manufacturing industry has been hit the hardest with “a nearly 60 percent jump” compared to pre-pandemic numbers. This “Great Resignation in Manufacturing” is the most of any industry, including hospitality, retail, and restaurants, which have seen about a 30% jump in resignations.

However, if you dig deeper, this trend isn’t new. This recent increase in job quitting in manufacturing has simply magnified a problem that had already been brewing for years, even prior to the start of the pandemic. In fact, in the four years prior to the pandemic (2015-2019), the average tenure rate in manufacture had decreased by 20% (US Bureau of Labor Statistics).

This accelerating workforce crisis is placing increased pressure on manufacturers and creating significant operational problems. The sector that was already stressed with a tight labor market, rapidly retiring baby-boomer generation, and the growing skills gap is now facing an increasingly unpredictable and diverse workforce. The variability in the workforce is making it difficult, if not impossible to meet safety and quality standards, or productivity goals. 

Manufacturing leaders’ new normal consists of shorter tenures, an unpredictable workforce, and the struggle to fill an unprecedented number of jobs. These leaders in the manufacturing sector are facing this reality and looking for ways to adjust to their new normal of building a flexible, safe and appealing workforce. As a result, managers are being forced to rethink traditional onboarding and training processes.  In fact, the entire “Hire to Retire” process needs to be re-imagined. It’s not the same workforce that our grandfather’s experienced, and it’s time for a change.

The Augmented, Flexible Workforce of the Future

The reality is that this problem is not going away. The Great Resignation in manufacturing has created a permanent shift, and manufacturers must begin to think about adapting their hiring, onboarding, and training processes to support the future workforce in manufacturing – an Augmented, Flexible Workforce.

What does this mean?

  • It means adopting new software tools to support a more efficient “hire to retire” process to enable companies to operate in a more flexible and resilient manner.
  • It means starting to understand your workforce at an individual level and using data to intelligently closes skills gaps at the moment of need and enables autonomous work.
  • And it means taking advantage of data.  More specifically, real-time workforce intelligence that can provide insights into training, guidance, and support needs.

Investing in AI-powered connected worker technology is one way to boost this operational resiliency. Many manufacturing companies are using digital Connected Worker technology and AI to transform how they hire, onboard, train, and deliver on-the-job guidance and support. AI-based connected worker software provides a data-driven approach that helps train, guide, and support today’s dynamic workforces by combining digital work instructions, remote collaboration, and advanced on-the-job training capabilities. 

As workers become more connected, manufacturers have access to a new rich source of activity, execution, and tribal data, and with proper AI tools can gain insights into areas where the largest improvement opportunities exist. Artificial Intelligence lays a data-driven foundation for continuous improvement in the areas of performance support, training, and workforce development, setting the stage to address the needs of today’s constantly changing workforce. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, contact us for a personalized demo.