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The Great Resignation in Manufacturing

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.

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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.

AI Manufacturing 2021 – Event Recap

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.

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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. 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”.

Modernizing Manufacturing Training with Continuous and Workflow Learning

Learn how continuous and workflow learning can help modernize employee training in the manufacturing industry.

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Staying ahead of the curve in today’s manufacturing marketplace means that businesses need to innovate and adapt. To accomplish this, organizations must have a skilled workforce and ongoing training and workforce management processes to support continuous learning and development.

Modernizing training cultivates employee skillsets by implementing continuous learning in the flow of work.

modernize manufacturing training with continuous learning

Continuous learning is the process of attaining new skills on a constant basis. Workflow learning involves educating yourself on the job using resources and self-directed learning materials. Done together, this modern training approach can help streamline productivity.

If you want to learn how to improve manufacturing training with continuous learning and workflow learning, explore this article that answers the following:

What is continuous learning?

Continuous learning in manufacturing involves enabling workers to learn new skills regularly. It’s a great way to improve employee performance and innovation. According to Forbes, embracing a culture of continuous learning can help organizations adapt to market demands, foster innovation, as well as attract and retain top talent.

Learning can come in different forms, from formal course training to hands-on experience. Employees are encouraged to be self-starters who want to evolve their skills on an on-going basis. A good example of a continuous learning model is everboarding; everboarding is a modern approach toward employee onboarding and training that shifts away from the traditional “one-and-done” onboarding model and recognizes learning as an ongoing process.

How can continuous learning be used in manufacturing?

When businesses don’t support continuous learning, manufacturing processes stagnate. This contributes to a lack of innovation and hinders potential opportunities for success that a company may experience.

In a nutshell, the more workers know and the more they can accomplish, the more they can contribute to business growth. This may consist of employees taking an online course or learning a new technique hands-on, no matter what department they’re in.

For example, assembly line workers may learn new manufacturing processes to ensure everything is functioning properly. Meanwhile, operators may study the latest machinery to learn new tricks of the trade.

What is workflow learning?

Workflow training in manufacturing involves learning while doing. This means that workers pick up new skills while on the job through hands-on experience.

The key to workflow learning is that it happens while employees perform their everyday tasks.

Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions. With workflow learning, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially bridging the gap between knowing and doing. This “active learning” aligns with the Pyramid of Learning visual model that illustrates the different stages of learning and their relative effectiveness.

pyramid of learning

Active learning involves the learner actively engaging with the material, often through problem-solving, discussion, or application of the knowledge while they are on the job.

In general, active learning is considered more effective than passive learning in promoting deep understanding and retention of information. Therefore, learning leaders often strive to design learning experiences that involve higher levels of active learning, moving beyond the lower levels of the pyramid and promoting critical thinking, creativity, and problem-solving skills.

How can workflow learning be used in manufacturing?

Workflow learning consists of using resources at your disposal to complete tasks. This strategy is sometimes referred to as performance support.

For example, workers can look up answers to questions, steps of a process, or new services while performing their jobs instead of interrupting their workflow to go to a class or training session.

Pro Tip

Active, or workflow learning 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.

A

How can technology improve manufacturing training?

The nature of manufacturing training is changing in the age of artificial intelligence. Today, many training processes can be streamlined and optimized using digital and smart, connected worker technologies.

For instance, data collected from everyday manufacturing processes can polish training programs online. Experienced workers can share best practices on customized dashboards for other employees to access. These can be updated in real-time and show changes highlighted to better optimize manufacturing processes.

Digital training tools can also help improve learning speed and retention. For example, workers who need visuals or real-world scenarios can assess them using AI-powered software to maximize their training.

 

Augmentir is the world’s leading AI-powered connected worker solution that helps industrial companies optimize the safety, quality, and productivity of the industrial frontline workforce. Contact us for a live demo, and learn why leading manufacturers are choosing us to elevate their manufacturing operations to the next level.

 

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How to Combat the Manufacturing Skills Gap with an Augmented Connected Workforce (ACWF)

Learn how manufacturers combat the manufacturing skilled labor shortage and close skills gaps with an Augmented Connected Workforce (ACWF).

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An Augmented Connected Workforce (ACWF) offers manufacturing and other industrial organizations a powerful solution to combat the ever-worsening skilled labor shortage and skills gap. According to a report by Deloitte and the Manufacturing Institute, an estimated 2.1 million manufacturing jobs could go unfilled by 2030 and the cost of those missing jobs could potentially total $1 trillion in 2030 alone.

augmented connected workforce acwf manufacturing

By integrating advanced technologies like artificial intelligence (AI), connected worker platforms, and other emerging solutions manufacturers can enhance the capabilities of their existing workforce and bridge skill gaps. Connected worker tools offer real-time monitoring of your frontline workforce, ensuring seamless operations. Moreover, connectivity enables remote collaboration, allowing experts to assist frontline workers from anywhere in the world. This interconnected ecosystem empowers workers with the tools they need to succeed and attracts new talent by showcasing a commitment to innovation and technology-driven growth.

Through an ACWF, manufacturers can effectively combat the manufacturing skilled labor shortage and close the skills gap while driving productivity, innovation, and remaining competitive. Read more about ACWF in manufacturing below:

Implementing an ACWF in Manufacturing

A critical element of transitioning from a traditional workforce to an Augmented Connected Workforce (ACWF) is implementing and adopting new technologies and processes. Here are a few steps that can help with the adoption of ACWF technologies and smooth transitions in industrial settings:

  • Step 1: Assess Current Processes – Organizations must understand existing workflows and identify areas where AI, connected worker platforms, and other ACWF technology can replace paper-based and manual processes to enhance efficiency and productivity.
  • Step 2: Invest in Technology – Procure  AI-driven analytics platforms, mobile technology, and wearable technology to enable real-time data collection and remote collaboration.
  • Step 3: Training and Onboarding – Provide comprehensive training programs to familiarize workers with new technologies and workflows. Emphasize the importance of safety protocols and data privacy.
  • Step 4: Pilot Programs – Start with small-scale pilot programs to test the effectiveness of the implemented technologies in real-world manufacturing environments. Target high-value use cases that can benefit from a transition from paper to digital.
  • Step 5: Continuous Improvement – Gather feedback from workers and supervisors during pilot programs and adapt implementation initiatives based on their input. Continuously optimize processes and technologies for maximum effectiveness.

By following these steps, manufacturers can smooth the transition from a traditional manufacturing workforce to an ACWF, empowering their frontline workers with improved capabilities, skills, and overall operational excellence.

Supporting Learning in the Flow of Work

Augmented Connected Workforce (ACWF) technologies allow for increased frontline support and for new processes around learning and training to strategically upskill and reskill, reduce time to competency for new workers, and to combat the skilled labor shortage in manufacturing and more. Connected worker tools, such as wearable devices and IoT sensors, enable real-time monitoring of worker performance and environmental conditions, ensuring safety and efficiency on the factory floor.

pyramid of learning

An ACWF also allows for improved workflow learning capabilities giving frontline workers access to expert guidance, remote assistance and collaboration, microlearning, and other learning in the flow of work options regardless of the worker’s location.

ACWF tools further enhance frontline activities through:

  • Digital work instructions and guidance: Smart, connected worker platforms provide digital work instructions, procedures, and visual guidance easily accessible to workers on mobile devices.
  • Digital mentors and training: Some ACWFs incorporate “digital mentors” – GenAI-powered industrial assistants that can provide step-by-step guidance to workers, especially new hires.
  • Knowledge capture and sharing: Connected frontline worker applications serve as knowledge sharing platforms, capturing data and insights from frontline workers, which can then be analyzed by AI software and used to improve processes, update work instructions, and share knowledge across the organization
  • Performance monitoring and feedback: ACWF solutions provide visibility into worker performance, allowing managers to identify areas where additional training or support is needed.

augmented connected workforce in manufacturing

In summary, ACWF initiatives empower frontline workers with the digital tools, knowledge, and support they need to learn and improve their skills directly within their daily workflows, rather than relying solely on formal training programs. This helps close skills gaps and drive continuous improvement.

Future-proofing Manufacturing Operations with an ACWF

Adopting an Augmented Connected Workforce (ACWF) approach centered around augmenting frontline workers with mobile technology, immersive training, collaborative decision-making, and continuous improvement, allows manufacturers to future-proof their operations and gain a sustainable competitive advantage. This concept empowers employees with powerful tools that augment and enhance their capabilities, productivity, and overall business processes by accessing critical information and fostering collaboration

AI-powered software can analyze vast amounts of data to optimize production processes and predict workforce development needs. At the same time, connected frontline worker solutions enable the integration of mobile and wearable technologies and provide real-time data insights, aiding in optimizing factory operations and adapting to evolving industry trends.

For an Augmented Connected Workforce, integrating AI and connected worker technologies serves as a vital strategy for manufacturers navigating the skilled labor crisis. Augmentir encourages organizations to embrace ACWF transformations and expedites adoption through a comprehensive connected worker platform leveraging the combined benefits of connected worker and AI technologies.

With Augmentir, frontline workers can access critical information, real-time data and insights, and expert advice and guidance all in the flow of work preventing lost time and improving both efficiency and productivity. Schedule a live demo to learn more about how an Augmented Connected Workforce future-proofs manufacturing operations and enhances frontline activities.

 

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How AI is Revolutionizing Manufacturing Training

Explore how Augmentir uses AI to personalize manufacturing training, boost performance, and deliver real-time support and content creation.

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In today’s fast-paced manufacturing environment, staying competitive means more than just upgrading equipment—it requires investing in people. But traditional workforce training methods haven’t kept up. Static instruction manuals, one-size-fits-all onboarding programs, and outdated SOPs often fall short of preparing workers for the dynamic challenges of the modern factory floor.

ai in manufacturing training

Enter artificial intelligence (AI). From analyzing worker performance to delivering personalized training and real-time support, AI is transforming how manufacturers develop and empower their frontline workforce. Solutions like Augmentir are at the forefront of this shift, using advanced analytics, machine learning, and generative AI to create more effective, agile, and personalized training ecosystems.

Here’s how AI is reshaping manufacturing training across four critical areas.

1. Smarter Upskilling and Reskilling Through Performance Analytics

One of AI’s most valuable contributions to manufacturing training is its ability to turn raw performance data into actionable insight. Every worker interaction—how long a task takes, whether they need help, how often they make mistakes—tells a story. Traditionally, these insights were anecdotal at best. With AI, they’re measurable and immediately useful.

Platforms like Augmentir use AI to analyze real-time worker performance data and automatically surface trends and gaps. Suppose a maintenance technician consistently struggles with certain procedures. The system flags this, allowing supervisors to deliver targeted retraining or create a learning path that addresses the weak areas. Likewise, workers who consistently perform well might be fast-tracked for cross-training or more advanced roles.

the difference between skills development and training in manufacturing

This approach enables continuous learning and ongoing upskilling and reskilling, not just during onboarding or annual reviews, but every day. By matching training efforts with actual needs—based on data, not guesswork—companies can build more agile, responsive workforces that are always learning and improving.

2. Personalized Work Instructions for Every Skill Level

Manufacturing is not a one-size-fits-all environment—so why should training be?

AI can help tailor work instructions and learning experiences to the individual. With Augmentir, for example, AI dynamically adjusts work instructions and guidance based on a worker’s experience, proficiency, and even recent performance. This personalization helps new employees ramp up faster and allows seasoned workers to bypass unnecessary detail and focus on what matters most.

For a novice, instructions might include step-by-step visual aids, safety warnings, and prompts for supervisor sign-off. A veteran might receive a streamlined checklist with optional references. The experience becomes smoother and more relevant for each person, improving accuracy and reducing the time it takes to perform tasks.

using ai to improve manufacturing trainingThis kind of adaptive guidance is especially valuable in high-mix, low-volume environments or where production processes change frequently. Workers stay productive while learning in the flow of work—a win for both efficiency and engagement.

3. On-the-Job Support with Generative AI Factory Assistants

Even the best training can’t prepare workers for every situation they’ll encounter. That’s where generative AI assistants—often called copilots—come in.

Imagine a frontline operator faced with an unfamiliar error code on a CNC machine. Instead of stopping work, digging through documentation, or calling a supervisor, they can ask an AI assistant integrated into their work app or wearable device. The assistant quickly provides context-aware help: maybe it’s a diagnostic procedure, a video walkthrough, or a simple checklist.

This is not science fiction—it’s happening now. With tools like Augmentir’s Augie, workers get real-time guidance, support, and training while they work, tailored to the exact task and situation. These industrial generative AI assistants learn and improve with each interaction, so the more they’re used, the better they get at helping.

augie generative ai assistant for manufacturing standard work

This not only boosts productivity but also reduces downtime, prevents errors, and improves worker confidence. AI copilots act like a mentor in your pocket—one that’s always available, always up to date, and always ready to help.

4. Rapid Content Creation with Generative AI Tools Like Augie

A major pain point in manufacturing training has always been content creation. Writing SOPs, training manuals, and onboarding documents is time-consuming, and keeping them current is a constant challenge—especially when processes, tools, or equipment change.

That’s where generative AI tools like Augmentir’s Augie come in.

Augie helps training teams and subject matter experts create up-to-date, accurate, and engaging content in a fraction of the time it used to take. You can input a few notes, a video walkthrough, or an old manual, and Augie will generate structured work instructions, training modules, or even interactive checklists. This democratizes content creation—now anyone from a line lead to a maintenance engineer can contribute training content without needing to be a technical writer.

augie industrial copilot generative ai assistant for training and quiz creation

More importantly, because Augie is part of the same ecosystem, the training content it generates can be immediately pushed into the hands of workers—embedded in digital workflows, accessible via AI assistants, or served up dynamically based on user behavior.

This means your training stays fresh, relevant, and aligned with the reality on the ground. No more outdated manuals. No more lag between process changes and training updates.

The Big Picture: AI as a Training Multiplier

What ties all these innovations together is a shift from static, one-time training to ongoing, personalized support—enabled by AI.

  • AI makes training smarter by identifying who needs help and where.
  • It makes training faster by delivering content that matches each worker’s needs.
  • It makes training more effective by embedding it directly into the flow of work.
  • And it makes training more scalable by automating content creation and support delivery.

In short, AI becomes a force multiplier for training. It empowers workers to get better faster, managers to lead more effectively, and companies to stay agile in a constantly changing world.

Looking Ahead

The manufacturing skills gap isn’t going away anytime soon. In fact, it’s projected that millions of manufacturing jobs could go unfilled over the next decade due to a shortage of trained workers. Traditional training methods simply can’t scale to meet this challenge.

But AI can.

By weaving intelligence into every layer of the training experience—from data analytics to real-time support—platforms like Augmentir offer a new blueprint for workforce development. It’s faster, smarter, more engaging, and ultimately, more human.

Because at the end of the day, it’s not about replacing people with AI—it’s about helping people thrive alongside it.

 

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This Is Not Your Grandfather’s Workforce

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

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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 and tacit 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.

How to Improve Manufacturing Employee Onboarding

Augmentir’s take on the trending Workforce Institute’s staggering survey numbers.

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Employee onboarding is crucial to any organization. It’s even more important in manufacturing, where workers have to understand complex operating procedures and accomplish tasks in a timely manner.

An employee’s first impression of a workplace can set the tone for their entire experience with the company. An engaging and informative onboarding process can improve job performance by setting up workers for success.

Plus, an employee is more likely to speak highly of the business they work for if they see themselves as a valuable member of the team.

If want to improve your manufacturing employee onboarding process, explore this article that goes over the following:

What is employee onboarding?

Employee onboarding is the process in which new hires are integrated into a company. It involves training activities, a new-hire orientation, and learning about the business’s structure, culture, mission and values.

Finding the right candidate for a position is the first step to building a successful team. Onboarding that new employee is the most important next step. Done right, this process can set the precedent for a productive, content and even excited worker.

The two main goals of the first day of onboarding should be to set clear employee expectations and introduce their objectives. Workers should know what their job duties and responsibilities are from the get-go.

How is onboarding different from employee orientation?

Onboarding is often confused with employee orientation. Orientation usually involves completing necessary paperwork, while the onboarding process is comprehensive and can last for months.

Employee orientation is a one-time event. Its purpose is to welcome new hires to a company and introduce a checklist of mandatory tasks to complete such as filling out forms.

Employee onboarding, meanwhile, consists of completing a series of activities, including orientation. It includes training over a longer period of time to help workers learn more about their roles, their teams and how their jobs relate to overarching company goals.

Both onboarding and orientation are critical aspects of introducing employees to their new work environment. They also complement each other in improving employee engagement.

How to effectively onboard new hires

Investing time in your workers is one of the best ways to retain employees and boost productivity.

A new hire’s first few weeks are some of the most important in setting up expectations and building their personal investment in your company.

Go above and beyond and you’ll reap the benefits. Overlook the onboarding experience and you could have unsatisfied employees.

Here are five ways to effectively onboard new hires:

Step 1: Create a worker playbook.

Start by giving a general overview of your business, including your mission, values and perks. Some things to include are:

  • Your customers and stakeholders
  • Work culture and expectations
  • Team members/employees
  • What company success and growth look like

Step 2: Set 90-day goals.

Giving new hires direction and actionable items from the start is important. Identify some goals to work towards to give employees the confidence to excel in the company.

Be sure to provide any resources they will need and connect employees with other workers who can help them. Having a clear plan will make it easier to track goals and collaborate with workers along the way.

Step 3: Set a time to meet and provide feedback.

Set aside time to meet with new hires to provide feedback and ask how they are doing. This can foster connectedness and engagement between you and your employee.

This also gives you the opportunity to learn more about your workers and address any concerns they may have.

It also lets you elicit employee observations of the company and its processes, which can be insightful. A new hire may offer ideas that people invested in the current paradigm wouldn’t think of.

Step 4: Outline schedule and job duties.

It’s crucial to set consistent work schedules to ensure productivity. Loose or frequently changing schedules can lead new hires to think your organization is disorganized.

Further, outlining job duties (such as required skills) can also give employees a sense of direction and ensure they have plenty to work on.

Consider digitizing your onboarding and training program to help accelerate the overall onboarding schedule and get your employees productive faster, and build a program that incorporates the following:

  • Job expectations
  • Performance evaluation
  • Role shadowing
  • Training opportunities
  • HR meetings/employee documentation
  • Compliance training
  • Ongoing assessment through quizzing

In time, new hires will have a better idea of their workload and how to create and execute their own daily task lists.

Step 5: Set up continuous learning opportunities.

The best results from onboarding come months after the process is over. That’s because setting up continuous employee learning opportunities fosters professional development.

A worker can take everything that they learned from the onboarding process and apply it to their day-to-day tasks. 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.

Why onboarding is important in manufacturing

Creating effective onboarding programs can boost employee engagement and create a manufacturing workforce that excels in industry-related skills.

Effective onboarding has also been shown to:

  • Reduce employee turnover
  • Cultivate existing and new skills
  • Integrate workers more quickly
  • Foster long-term employee satisfaction
  • Create the foundation for workforce development

Optimizing onboarding with connected worker technology

Many manufacturing companies are using modern connected worker technology to transform and optimize 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 digital tools can gain insights into areas where the largest improvement opportunities exist. Today’s workers embrace change and expect technology, support and modern tools to help them do their jobs.

Augmentir’s AI-based connected worker solution delivers continuous learning and development tools to optimize onboarding training for a rapidly changing and diverse workforce.

Built-in reporting for skills management and job proficiency allows you to accurately track and manage skills, certifications, and qualifications for your team. AI-based analytics help you better understand your workforce and make informed workforce development decisions.

intelligently assign jobs

Find out how our software can make it easier to onboard new employees and set them up for success. Contact us today to arrange a demo.

Say Hello to Augie!

Say hello to the newest addition to the Augmentir platform, Augie – the GenAI powered digital assistant for manufacturing.

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Say hello to the future of work in manufacturing with the latest addition to Augmentir’s suite of connected worker tools, Augie™.

augie generative ai assistant for manufacturing

Augie is a digital assistant for frontline operations that utilizes Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) to enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. It leverages enterprise-wide data, provides instant access to relevant information, closes skills gaps with personalized support, offers insights into standard work and skills inventory, and identifies opportunities for continuous improvement.

Augie is a result of our dedication to empowering frontline workers, leveraging AI to support manufacturing operations, and giving manufacturing workers better tools to do their jobs safely and more efficiently.

Continue reading below to learn more about how Augie works and how it can benefit your frontline workforce and manufacturing operations:

How our GenAI Powered Assistant Works

Generative AI-powered smart manufacturing assistants are designed to provide secure, role-based, personalized assistance to frontline workers, engineers, and managers in various industries, including manufacturing.

They work by leveraging artificial intelligence and integrations across different software systems, providing guidance and assistance in various tasks to enhance productivity and performance. This includes providing data insights, recommendations on actions to improve performance, and the ability to create analyses and dashboards with a natural language-based assistant.

A majority of smart manufacturing assistants only draw their information from manufacturing execution systems (MES), without tying in other important systems necessary for frontline manufacturing success.

Augie, however, is different. It leverages enterprise-wide data tying in information from a wide range of platforms including operational data, training and workforce management data, connected worker and engineering data, as well as information from enterprise systems.

gen ai industrial manufacturing

How Augie Benefits Your Frontline Workforce

Augie is unique among other smart manufacturing assistants. It leverages proprietary fit-for-purpose, pre-trained LLMs and generative AI, coupled with robust security and permissions, to help factory managers, operators, and engineers improve efficiency, resolve issues faster, and prevent downtime.

With information readily available via Augie, frontline workers can make decisions faster, reduce downtime, and improve troubleshooting with instant access to summarized facts relevant to a job or task. Additionally, Augie is multi-modal, meaning it can return actionable information in the form of work procedures, training videos, recorded collaborations, engineering documents and SOPs, as well as tribal knowledge.

Through Augie, manufacturers can instantly:

  • Close skills and experience gaps with personalized support
  • Gain insights into Leader Standard Work
  • Gain new insights into skills inventories
  • Convert Tribal Knowledge into Digital Corporate Assets
  • Identify opportunities for continuous improvement
  • Forecast potential operational issues

augie gen ai industrial assistant troubleshooting

With Augie by your side, you can streamline manufacturing operations, optimize performance, empower your frontline workforces, and stay ahead in today’s rapidly evolving and competitive landscape.

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Improve Operational Efficiency with Augie and Augmentir

The digitization of frontline processes has become a must-have to keep up with the velocity of change – but not just digitization … smart digitization. Recently, Deloitte found that 86% of manufacturing executives believe smart factory solutions will be the primary drivers of competitiveness in the next five years. Leveraging smart, AI-driven connected worker solutions that allow industrial organizations to best support their frontline workforces and optimize processes to make them safer and more efficient is critical to overall enterprise success.

At Augmentir, we have been met with continued success in our efforts to transform manufacturing operations. Our patented Smart AI foundation helps manufacturing organizations close the loop between training and work execution, delivering the data and in-line insights necessary to continuously improve operational excellence day-over-day, year-over-year. Augmentir is the world’s leading connected worker solution, combining smart connected worker and GenAI technologies to drive continuous improvement and enhance performance management initiatives in manufacturing.

The addition of Augie to our platform is a game-changer for factory floor and other frontline workers, allowing for quick reference troubleshooting and useful, contextualized information to be delivered at the moment of need. Furthermore, with Augie, less experienced workers are provided with additional support and individualized guidance based on the job or task needs.

With patented AI-driven insights that digitize and optimize manufacturing workflows, training and development, workforce allocation, and operational excellence, Augmentir is trusted by manufacturing leaders as a digital transformation partner delivering measurable results across operations. Schedule a live demo today to learn more.

 

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