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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”.

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, 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.  

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 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.

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.

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 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. 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.

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.

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 “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 workforce is changing in real-time – who shows up, what their skills are, what jobs they need to do, is a constantly moving target. The traditional “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 the skilled workers issue 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, significantly reducing onboarding time. 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.