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Join Chris Kuntz for an interview Packaging Insights on how AI and connected worker technology can help the packaging industry overcome the skilled labor crisis.

The packaging industry has been hit by the low availability of skilled workers, but for Chris Kuntz, VP of Strategic Operations at Augmentir, AI systems offer the solution. In this interview with Joshua Poole from Packaging Insights, Chris explores how AI and the Augmented Connected Workforce could revolutionize the packaging industry and how Augmentir’s AI-powered connected worker solution supports optimal efficiencies in manufacturing. He also discusses the importance of effective regulatory frameworks for AI.

This transcript has been edited for clarity and length. View the original video interview on the Packaging Insights website here.

packaging industry connected workforce

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Joshua Poole: Hello, everyone. My name is Joshua Poole, and I am the editorial team leader at CNS Media, the publisher of Packaging Insights. I am very pleased to be joined today by Chris Kuntz, who is the Vice President of Strategy at Augmentir, and who is here to talk about the benefits of AI in relation to the packaging industry.

So welcome to you, Chris.

Chris Kuntz: Thank you very much, and thanks for having me, Joshua.

Joshua Poole: So, Chris, AI systems are expected to really transform the wider society but in relation to the packaging industry, to what extent could they revolutionize operations there?

Chris Kuntz: The reality is, to a huge extent. The impact centers around the manufacturing workforce – the people that are part of manufacturing. Historically, the application of AI, artificial intelligence, and machine learning, in manufacturing anyway, has focused on automating repetitive lower-level processes, that replace humans in the factory. Today, what we need to think about, and what we focus on here at Augmentir, is how we can use AI to augment the human workforce. And so, AI, again, used throughout the industry, its served great application from a predictive maintenance, machine failure standpoint, energy efficiency – things like resource utilization and even supply chain visibility and quality control.

And those applications of AI in manufacturing will continue to provide value. But the reality is people are still needed in paper mills, on the factory floor in the areas of safety, quality, and maintenance. There are jobs that just require that humans are there. And that’s not going away any time soon. But what we are faced with, and what many manufacturers are faced with, is these workforce challenges of the aging workforce, the retiring workforce going away. They’re walking out the door with a vast amount of knowledge that is essential to operate factories and plants. Pre-pandemic we had an emerging workforce coming in that maybe didn’t have the necessary skills, but today post-pandemic era, there’s a massive job shortage. There are no workers coming in, and so manufacturers are forced to look at a pool of less-skilled workers to perform tasks that they may not be initially qualified for.

So, it is not just that the skilled labor is going out, it’s just that we don’t have any skills coming in. And so, every manufacturer is faced with a massive labor shortage and as a result a massive shortage of skills required to operate successfully any given day on the shop floor. And that’s really where we think the value is going to come from an AI standpoint, and it’s kind of transformative when you look at historically the application of AI in manufacturing.

Joshua Poole: So, you mentioned the industry is really struggling to overcome the lack of a qualified workforce. How can AI overcome this problem across the industry?

Chris Kuntz: One of the great things about artificial intelligence, and our history as a company, and one of our previous companies was focused on collecting data from connected machines and then using that data and analyzing that data with AI to understand how to make those machines operate better and improve those machines.

From a human standpoint, humans have been relatively disconnected on the shop floor. They’re using paper-based checklists and SOPs and work procedures, the same sort of technology they were using 20, 30 years ago. So, they’re relatively disconnected, and we know little about how they’re operating and how they’re performing and where they need help and where they need assistance.

If we can connect those workers – and I am talking connecting with phones, tablets, wearable devices – if we can connect those workers we have a digital portal into how they’re performing, and through AI we can analyze how they’re performing and then offer them real-time guidance almost like an AI assistant that’s sitting there helping them out if they are struggling, helping them out if they need help, guidance, or support, or if there is a potential safety or security issue that they might be running into.

The same way that AI has historically been used to act on machine data to improve machine efficiency and performance, we can use the same approach for the humans in the factory.

Joshua Poole: Mm-hmm, and can you provide any examples of the ways in which your platform, Augmentir, has benefited companies looking to embrace AI to improve their operations?

Chris Kuntz: Yes, there are a few different ways. More recently we just launched our Generative AI assistant called Augie™. And what that does is that allows workers or operations managers, using natural language, to solve problems faster, assist in troubleshooting, and provide guidance when needed.

One of the first use cases is troubleshooting. This happens every day in a plant, in a paper mill, it happens every day – there’s a problem with a machine, we need to get it back up and running. Otherwise, there’s a downtime issue, which leads to production/revenue loss. And it’s not a standard procedure to fix the machine. And so there’s troubleshooting that needs to happen. This process is very collaborative. But also from a worker standpoint, they typically have to go to 5, 6, 10 different systems to try to find information or talk to different people.

And what a Generative AI assistant can do is be that digital front end to all that wealth of information and return information on, “Hey here’s the solution to this problem. It’s been solved before, it’s in this published guide, here you go.” Or, “You may want refer at this work procedure. This is something, a troubleshooting guide that could help you solve the problem.” Or, “Here’s a subject matter expert that exists” and you can remotely connect to this person who has expertise in this particular type of equipment.

And so being able to give real-time access to that individual at the time of need is critical. And I think the other big area, at least early on here, is around training.

So, if you think about the skilled labor, workforce shortage, the tenure rates in manufacturing, people are quitting faster. They’re not sticking around for 15 years, they’re sticking around for three years, maybe, possibly, at max. And so, training and learning and development, HR leaders have to think about how to change onboarding practices because it’s not practical anymore to onboard someone for six months if they’re only gonna be around for nine months.

And so the goal, with many of the organizations that we speak with, the goal is to reimagine and rethink training and move it away from the before they’re productive in the classroom to move it onto the floor. Move it into the flow of work, they call it. And so what we can do with AI there is, we don’t understand that worker or their skill level or their competency levels. And if that’s digitally tracked, we can use AI to augment those work instructions and work procedures to say, “Hey, you’re a novice. This is your first month on the job. You’re required to watch this safety video before you do this routine.” And if you’re an expert worker, maybe you wouldn’t be required to do that. Or if you were trained, but your performance is lagging vs. the benchmark, we can come – the instructions can come and be dynamically adjusted to say, “Hey, here’s some additional guidance to help you through this procedure and through this routine.”

So, it gives visibility and insight into areas. I mean, if you had three people on the shop floor, you’d probably know exactly what they were doing. But once you get some larger organizations and they have dozens of people or hundreds of people, it becomes much much harder to understand where the opportunities for improvement are. And AI has the ability to do that, certainly in the training area.

Joshua Poole: Hmm, that’s very interesting. And of course, AI is largely unregulated worldwide, which can create problems like AI washing and irresponsible use. But what do you see as the biggest concern with the proliferation of AI systems within the packaging industry?

Chris Kuntz: So, certainly there’s a lot of concerns with respect to that, and for Augmentir, our approach is we leverage a – certainly from a Generative AI standpoint, we leverage a proprietary, fit-for-purpose, pre-trained large language model that sits behind our Generative AI solution. And when you combine that with robust security and permissions that can help factory managers, operators, and ever engineers or frontline workers only have access to the information that they need, and still provide the benefits of problem-solving faster and improved collaboration.

One of the other things though that I think is really important is this concept of “verified content” – so we’ve all used ChatGPT, right? And early on, I think they had this disclaimer, ChatGPT is 90% correct, so it could return false data. That’s not just not acceptable in an industrial settting. You can’t say, “Here’s a routine to do a centerlining on a piece of equipment” and have someone stick their hand in a place and get it chopped off. You can’t be 90%, you have to be 100%.

So, we have a concept of our Generative AI system, the ability to return verified and unverified data, and then the organization can decide what they want to do with that. So, if it’s a frontline worker, maybe, if it is unverified data, it’s labeled, and you need a supervisor that has to come over if you are going to perform that routine. And then the ability to sort of take the information that comes back and categorize it in terms of verified data, unverified data, and then be able to control how you’re using that. So, it’s not the wild wild west, it’s a very controlled environment. The scope of, if you think about our, in our world, if we’re serving a manufacturing company – and Augmentir is being used for digital manufacturing in paper and packaging companies like Graphic Packaging and WestRock, and so the information that, in our scope of their world is corporate documentation, engineering documentation, operational data, work order data, people data – could be their skills matrix and training history and things like that, but it’s all contained within their enterprise. We’re not looking outside of that, it’s really a constrained data set. And that’s what feeds our large language model.

That significantly helps the application of this, there are people that are exploring using more open AI and GPT models to do this. But then you run into the problems that you said, where there’s a lot of information that both you are feeding into the AI, which could be a security risk, and then the information that you are getting back that could be a security risk.

Joshua Poole: Okay, and as a final question. What advice would you give to politicians working to establish these regulatory frameworks for AI systems?

Chris Kuntz: Great question.

You know, our point of view is we think, you know President Biden had the AI regulation executive order here in the United States back in October, we think it’s much needed on several fronts. Certainly, every company now is saying that they’re an AI company and trying to sprinkle in AI to everything they do. And some of that can be a little problematic.

But at least in the U.S. here in Biden’s AI regulation executive order, there was a lot of talk about job disruptions and putting focus on the labor and union concerns related to AI policies. I think that reinforces our use of AI as a way to augment workers. We’re not looking to replace workers and it’s addressing a huge problem. I think the Department of Labor, they’re issuing guidance to employers around AI that you can’t use it to track workers and you can’t use it to, you know there’s labor rights that exist in the world. And I think that gets back to having these AI co-pilots or Generative AI assistants that can help workers perform their jobs safely and correctly, maximizing the potential. It’s really where on-the-job learning comes into play. It’s things that were happening off the factory floor before. Now it’s squarely suited to help address some of the big manufacturing labor workforce problems that exist today. So, there’s a lot of language in that executive order around making sure that AI is used, not just responsibly, but used for purposes that are going to further the industry. And again, that’s squarely where we sit in terms of workforce development and using it to address the labor shortages from a training and support standpoint.

But, overall, I think, absolutely we embrace the regulatory – Generative AI regulation – and control aspects of this because it could become problematic if you are not doing that, for sure.

Joshua Poole: Mm-Hmm that’s very interesting. Chris, thanks for your time today.

Chris Kuntz: Yes, thank you very much. Thanks for having me.

 

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

The evolution of artificial intelligence and machine learning technologies in manufacturing has seen tremendous growth over the past few decades, with astounding leaps in technology and industry-wide transformations.

evolution of ai in manufacturing

Dating back to the 1960’s, manufacturers started using AI in robotics and basic automation. This early usage focused on automating manual, highly repetitive human tasks such as assembly, parts handling, and sorting, allowing for higher levels of production and efficiency.

Over time, this evolved with AI-enabled machine vision systems, which were used to automate visual inspections, allowing for better quality control and precision during production cycles. More recently, AI has been at the center of warehouse automation, as well as the Industrial Internet of Things (IIoT), where physical machines and equipment are embedded with sensors and other technology for the purpose of connecting and exchanging data, which is used in predictive analytics for machine health monitoring. Manufacturers can now glean valuable insights from data collected over time about optimizing their operations for maximum efficiency without sacrificing quality.

Despite the breath of applications that AI has in the industrial setting, there is a common thread across all of the above examples – AI has largely been used to automate highly repetitive or manual tasks, or perform functions designed to replace the human worker.

However, these examples laid the groundwork for the adoption of AI in manufacturing and for the use of AI technologies that augment and directly support frontline workers today.

Read below for more information on how the use of AI and GenAI is evolving in manufacturing, and being used to augment the human worker, transforming productivity and efficiency at a time when workforce optimization is needed most.

Using AI to Augment, not Replace the Workers in our Factories

Today, AI technologies in manufacturing have evolved to encompass a diverse range of applications. According to Deloitte, 86% of surveyed manufacturing executives believe that AI-based factory solutions will be the primary drivers of competitiveness in the next five years. Robotics and automation have become more adaptive and collaborative, working alongside and augmenting human workers to streamline production processes and increase efficiency – rather than simply trying to replace them.

As computing power and algorithmic capabilities improved, AI in manufacturing has become more advanced and widespread. The emergence of Industry 4.0, characterized by the convergence of digital technologies, further accelerated AI’s role in manufacturing. By leveraging tools like connected worker solutions to gather frontline data, manufacturing organizations can now capitalize on AI’s extraordinary computing power to analyze that data and derive actionable insights, improved processes, and more.

Much like the industry has learned to optimize equipment from the 1.7 Petabytes of connected machine data that is being collected yearly, we are now able to optimize frontline work processes and people from highly granular connected worker data, with one major caveat: In order to leverage this incredibly noisy data, a system has to be designed with an AI-first strategy, where the streaming and processing of this data is intrinsic to the platform – not added as an afterthought.

The potential for AI to help augment the human worker is there, but why now?

Because for today’s manufacturers, time is not on your side.

The workforce crisis in manufacturing is accelerating, and at the forefront of the minds of Operations and HR leaders. Job quitting is up, tenure rates are down, and manufacturers struggle daily to find the skilled staff necessary to meet production and quality goals. The threat is huge – with significant impacts to safety, quality, and productivity.

AI-based connected worker solutions allow industrial companies to digitize and optimize processes that support frontline workers from “hire to retire”. These solutions leverage data from your connected workforce to optimize training investments and proactively support workers on the job, across a range of manufacturing use cases.

 

paperless factory

Furthermore, solutions that leverage Generative AI and proprietary fit-for-purpose, pre-trained Large Language Models (LLMs) can enhance operational efficiency, problem-solving, and decision-making for today’s less experienced frontline industrial workers. Generative AI assistants can leverage 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.

Augmentir’s AI-First Journey

At Augmentir, since the beginning, we pioneered an AI-first approach toward manufacturing and connected frontline worker support. 

augmentir's ai-first journey

Many manufacturing solutions incorporated AI technology as an add-on or afterthought as the technology gained more advanced capabilities and popularity. We, however, have been championing and building a suite of solutions using AI as a foundation. Our platform was designed from the bottom up with AI capabilities in mind, placing us as a leader in the connected frontline worker field. 

  • 2019 – Augmentir launched the world’s first AI-first connected platform for manufacturing work empowering frontline workers to perform their jobs with higher quality and increased productivity while driving continuous improvement across the organization. This marked the start of our AI-first journey, giving industrial organizations the ability to digitize human-centric work processes into fully augmented procedures, providing interactive guidance, on-demand training, and remote expert support to improve productivity and quality.
  • 2020 – Augmentir unveiled True Opportunity™, the first AI-based workforce metric designed to help improve operational outcomes and frontline worker productivity through our proprietary machine learning algorithms. These algorithms take in frontline worker data, then combine it with other Augmentir and enterprise data to uncover and rank the largest capturable opportunities and then predict the effort required to capture them.
  • 2021 – Building on user feedback and field data, Augmentir reveals True Opportunity 2.0™, with improved and enhanced capabilities surrounding workforce development, quantification of work processes, benchmarking, and proficiency. By Leveraging anonymized data from millions of job executions to significantly improve and expand the platform’s ability and automatically deliver in-app AI insights we were able to increase benefits and returns for Augmentir customers.
  • 2022 – Augmentir announces the release of True Productivity™ and True Performance™. True Productivity allows industrial organizations to stack rank their largest productivity opportunities across all work processes to focus continuous improvement teams at the highest ROI and True Performance determines the proficiency of every worker at every task or skill enabling truly personalized workforce development investments.
  • 2023 – Augmentir launches Augie™ – the GenAI-powered assistant for industrial work. By incorporating the foundational technology underpinning generative AI tools like ChatGPT, we enhanced our already robust offering of AI insights and analytics. Augie adds to this, improving operational efficiency and supporting today’s less experienced frontline workforce through faster problem-solving, proactive insights, and enhanced decision-making.
  • 2024 – As this year progresses, we have already continued to refine our AI-first solutions and apply user feedback and additional features to best support frontline industrial activities and workers everywhere.
  • 2025 and beyond – True Engagement™, looking forward we predict the evolution of AI in manufacturing activities will continue, progressing until we can accurately measure signals to detect the actual engagement of industrial workers and derive useful information and insights to further enhance both HR and manufacturing processes.

We are deeply involved in applying AI and emerging technologies to manufacturing activities to augment frontline workers, not replace them. Providing enhanced support, access to key knowledge (when and where it does the most good), and improving overall operational efficiency and productivity.

The Future of AI in Manufacturing – The Journey Forward

As we press onward into the future, we at Augmentir are determined to champion the application of AI and smart manufacturing to augment and enhance frontline workers and industrial processes. We will continue to evolve our application of AI and its use cases in manufacturing to help frontline teams and workforces, reinforcing our AI-first pedigree.

The addition of Augie to our existing AI-powered connected worker solution is an important step forward. Augie is a Generative AI assistant that uses 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.

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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AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data, and personalized instruction.

Deloitte recently published an article with the Wall Street Journal covering how AI is revolutionizing how humans work and its transformative impact. They emphasized that AI is not merely a resource or tool, but, that it serves almost as a co-worker, enhancing work processes and efficiency. This article discussed how the evolving form of intelligence augments human thinking and emphasized this as a catalyst for accelerated innovation.

Manufacturing is uniquely situated to benefit from AI to improve operations and empower their frontline workforces. The skilled labor gap has reached critical levels, and the market is under tremendous stress to keep up with growing consumer demand while staying compliant with quality and safety standards. Manufacturing workers are crucial to the success of operations – maintenance, quality control and assurance, and more – manufacturers rely upon their workforce to ensure production proceeds smoothly and successfully.

AI is playing a key role in changing the manufacturing landscape, augmenting workers and empowering them with improved, optimized processes, better data for informed decision-making, troubleshooting, personalized instructions and training, and improved quality assurance and control. According to the World Economic Forum, an estimated 87% of manufacturing companies have accelerated their digitalization over the past year, the IDC states 40% of digital transformations will be supported by AI, and a recent study from LNS Research found that 52% of industrial transformation (IX) leaders are deploying connected worker applications to help their frontline workforces. Not only that, AI technology is expected to create nearly 12 million more jobs in the manufacturing industry.

Integrating AI into manufacturing not only enhances productivity, but also opens the door to new possibilities for worker safety, training, and innovative new manufacturing practices. Here are some ways AI is transforming manufacturing operations:

  • AI-based Workforce Analytics: Collecting, analyzing, and using frontline worker data to assess individual and team performance, optimize upskilling and reskilling opportunities, increase engagement, reduce burnout, and boost productivity.
  • Personalized Training in the Flow of Work: With AI and connected worker solutions, manufacturers can identify and supply training at the time of need that is personalized to each individual and the task at hand.
  • Personalized Work Instructions: AI enables manufacturers to offer customized digital work instructions mapped to their skill levels and intelligently assign work based on each individual’s capabilities.
  • Digital Performance Support and Troubleshooting Guide: Generative AI assistants and bot-based AI virtual assistants offer support and guidance to manufacturing operators, enabling access to collaborative technologies and knowledge bases to ensure the correct actions and processes are taken.
  • Optimize Maintenance Programs: AI algorithms analyze data from sensors on machinery and other connected solutions to predict when equipment is likely to fail. This enables proactive maintenance, minimizing downtime and reducing maintenance costs. Additionally, with AI technologies, manufacturers can implement autonomous maintenance processes through a combination of digital work instructions and real-time collaboration tools. This allows operators to independently complete maintenance tasks at peak performance.
  • Improve Quality Control: AI-powered solutions can improve inspection accuracy and optimize quality control and assurance processes to identify defects faster. With connected worker solutions, manufacturers can effectively turn their frontline workforce into human sensors supplying quality data and enhancing assurance processes.
  • Ensure Worker Safety: AI-driven safety systems coupled with connected worker technologies monitor the work environment, supplying real-time data and identifying potential hazards to ensure a safer workplace for employees.

connected enterprise

As AI continues to advance, the manufacturing industry is poised for even greater transformation, improving both the quality of products and the working conditions for employees. AI is revolutionizing the way humans work and how the manufacturing industry approaches nearly every process across operations, augmenting work interactions, productivity, efficiency, and boosting innovation.

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.

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

Everyone is talking about it. The skilled labor shortage. It’s not a temporary problem. It’s here to stay. So instead of panicking and trying to use the same old strategies to identify, recruit and retain the increasingly rare skilled and experienced worker, let us present a different way of looking at the labor challenge. Spoiler alert: we see opportunity!

But first, let’s unpack some recent survey findings about the labor market. 

According to a survey by the Workforce Institute, a whopping 87 percent of manufacturers are feeling the ramifications of the shortage of skilled labor, including staff misalignment along the production lines, burnout, and supply chain disruption. 

Finding workers with the right skills, education and certifications can feel like looking for a needle in a haystack–hopeless and painful. The shrinking talent pool is forcing companies to rehire former employees who previously quit with limited skills or individuals with no manufacturing experience; it probably feels like the only viable option for production survival.

Where do you start with this new variable workforce? Standardized training programs? Excel spreadsheets for tracking and monitoring? These methods pose a concern for all workers on your production lines, regardless of their experience or skill set. Who needs what training? Who is responsible for tracking productivity and capturing relevant data? How confident are you in endorsing skills and assigning production teams with limited or imprecise information?

The old way would have led to panic. Today, there’s a better, smarter way. Today’s variable workforce in the manufacturing world is perfectly suited to adopt smart technology that will reduce, if not eliminate, the challenges associated with the labor shortage. Remember that thing we said about opportunity? Here it is.

Stay calm and carry on: smart digital tech can have an immediate and direct impact on learning about and managing worker skills.

Imagine if you could learn about a worker’s skills by tracking their performance in real time, immediately deliver training resources tailored to them based on their proficiency and certifications and then match them confidently to a production team where they’ll make a meaningful contribution. Sound like wishful thinking? It’s not.

Smart connected worker technology can collect data on worker patterns by tracking their performance journeys. It pulls relevant resources from the company inventory to deliver customized training programs. With the right training in place workers are engaged and feel safe while performing tasks. And, your teams are equipped to meet productivity goals.

The labor shortage is just a statistic. A smart connected worker suite is the solution.

Augmentir’s smart connected worker suite closes the gap between training and worker execution. Digitized instruction and skills management programs display and organize workers’ proficiencies based on levels of expertise. AI-driven insights monitor and easily match workers with procedures by assigning skills criteria. This proprietary Smart AI technology intelligently prompts workers for continuous training and accurately identifies appropriate skills endorsements to managers, helping them create better production lines. It’s the only solution of its kind on the market.

Kylene Zenk, Director of the Manufacturing Practice at UKG sees opportunity, too:

“If you can offer training or can tailor a job to meet candidates’ flexible qualifications, filling open headcount becomes more realistic in a tight labor market.”

We couldn’t agree more. Find out more about how and why manufacturers are taking smarter approaches to building a strong talent pipeline with Augmentir. Contact us for a demo today.

Smart Skills Management software is helping manufacturers bridge the gap between training, skills, and work to build a more resilient and agile workforce.

Where are you on your journey with adopting new and emerging technologies? Many manufacturers are jumping on the bandwagon for some of the latest tools that provide digital guidance to workers. Maybe you decided to implement digital work instructions to help workers safely and efficiently perform tasks. Or maybe you’ve bought skills management software to help you catalog and organize the skills and capabilities of different workers. But are either of these enough on their own to achieve all your production goals? Possibly, but unlikely.

Digital work instructions on their own deliver standard work guidelines but fail to consider the unique skills of each worker. Standalone skills management programs may offer a highlight reel of the skills and certifications of your workers but neglect to capture performance in real-time to provide accurate skills evaluations. Nor do they offer personalized training content needed to ensure workers perform their absolute best. Can we agree then these two features should go hand-in-hand?

One cannot exist without the other: Blending skills into the flow of work

In the past, standalone skills management systems were sufficient because:

  • Turnover was infrequent so line supervisors knew everyone on their team and their current skills and endorsements, making it easy for the supervisor to assign work safely and optimally
  • Investments in training, reskilling, and upskilling were performed either in a one size fits all approach or through a purely subjective or anecdotal approach

Today, however, a different situation exists.

Line supervisors are dealing with team members that they don’t know well, new ones starting every day, and experienced ones leaving.  This creates safety issues and makes optimally assigning work difficult as not only are the workers variable, but their skill levels and certifications are a constantly moving target.

An integrated, closed-loop skills management system is the solution for this era of high workforce turnover and absenteeism.

 

skills and work

 

Skills management solutions that combine skills tracking capabilities with connected worker technology and on-the-job digital guidance can deliver significant additional value. Data from actual work performance can inform workforce development initiatives allowing you to target your training, reskilling, and upskilling efforts where they have the largest impact.

It can generate an abundance of valuable data to provide tailored training support and skills endorsements and identify workforce opportunities. What else is possible? Imagine reducing training costs, optimizing job scheduling, increasing safety, and improving productivity. And now consider what will happen when you add smart technology to this all-in-one package.

 

intelligently assign jobs

The power of smart digitization! Skills management and digital work instructions together boost productivity.

According to Deloitte, organizations are shifting to a skills-based approach to meet the demand for agility, agency, and equity. Connected worker solutions that combine skills management with digital work instructions, collaboration, and knowledge management are uniquely suited to optimize today’s variable workforce. AI-generated insights are pulled from patterns identified across all work activity in real-time. These insights identify where new and experienced workers may benefit from either reskilling or upskilling.

This combination of smart digital technology can also leverage your training resources, such as instructional videos, written instructions, or access to remote experts, to deliver personalized guidance for the worker to perform their best. These tools intelligently work together to help you assign workers to procedures based on required skill levels. No second guessing! Augmentir is the only smart connected worker solution to intertwine these management tools with AI making it a powerhouse for optimizing your operations and meeting production targets.

 

 

Learn how Smart Skills Management software is helping manufacturers bridge the gap between training, skills, and work to build a more resilient and agile workforce.

Download our latest eBook – The Future of Work: Connecting Skills Management with Standard Work.

 

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

Do you remember when offshoring–the outsourcing of production internationally–was once considered the “gold standard” for manufacturers because of reduced costs? Funny how things change. We can partly thank the global pandemic for this. Reshoring, also referred to as ‘onshoring’, in manufacturing is now the way to go–the apparent panacea to supply chain disruptions and a healthier economy. This should have manufacturers cheering and dancing in the streets, right? Not so fast. We’ve also got a massive labor shortage to deal with. But don’t fret. There are solutions to be found, and they happen to exist in software tools already being embraced by organizations on their journey to digital transformation.

The perks and pressures of onshoring in manufacturing

If your organization isn’t already thinking about onshoring its operations, maybe you should be. Onshoring in manufacturing means greater resiliency, agility, and sustainability by shortening the distances between process and delivery. Less travel means reduced emissions and adherence to ESG standards. Reshoring addresses issues associated with shipping costs, lead times, and new regulations. Working in familiar markets can help identify supply and demand trends more accurately. National employment rates are likely to increase when hiring residents and working with other domestic business partners.

But labor shortages and the variability of today’s workforce have not made reshoring an easy shift. So while there is tremendous opportunity to bring production home, the lack of affordable and skilled labor is having a tremendous impact on our domestic production capacity.

Here’s how you make onshoring work for you. First, stop thinking the old way of recruiting, training, and retaining workers will still work today.

Work with what you’ve got

What’s wrong with training today? Yes, training programs can help improve worker knowledge and skills development. But only if they are meeting the unique needs of individual workers with content-rich, high-impact learning and hands-on training programs. Forget those standard training programs–they are useless in the face of the variable workforce we have available today. The workers you can find are showing up with a mixed bag of experience and skills. That doesn’t have to be a disadvantage anymore. Because there is a smarter way to train and optimize the skills of each of those workers to meet productivity goals individually and fulfill the potential for your organization’s production capacity.

Smart digitization is the ticket to effective onboarding, training, and more–from hire to retire

“The secret of change is to focus all your energy not on fighting the old, but on building the new.” – Socrates

This new era of workforce instability is forcing manufacturers to change. It’s forcing them to turn to digital technology and look at smarter ways to hire, onboard, train, and retain their workers. At Augmentir, we call this Smart Digitization.

What do we mean by ‘smart’ digitization? Smart digitization involves adopting modern, digital tools, mobile technology, and supporting workers throughout their entire lifecycle.

smart digitization throughout worker lifecycle

 

Modern connected worker tools are at the core of the solution that supports workers throughout their employment, from training to troubleshooting in real-time to ongoing learning and development. If you look at the entire employee lifecycle, this means:

  1. Using software tools to digitize and automate onboarding and skills tracking to help get workers operational faster, regardless of their skill and experience.
  2. Once on the job, digitizing and personalizing work instructions based on the individual needs of the worker – whether they are a novice worker or an expert.
  3. Proving instant access to support, within the flow of work.
  4. And finally, using an AI-based system to analyze how workers are performing on the job, and intelligently targeting upskilling and reskilling based on actual work performance.

Workers have access to a suite of digital tools and knowledge resources at their fingertips – digital work instructions, collaboration, and support tools to guide them on the job and quickly problem-solve complex tasks, allowing them to do their personal best.

For employers, this means not only more engaged and collaborative workers, it also means deeper insights into work performance that can help drive continuous improvement efforts.

skills job proficiency mapping

AI-based smart insights intelligently optimize workers’ performance by identifying and tracking their skills in real-time. Smart insights pull from these performance metrics and learn to prompt workers who need new training programs or work opportunities, continuously upskilling and reskilling.

It’s the advanced medicine needed to maximize productivity and operational health.

So as you plan to bring more of your production back home, make sure you’re ready to seize the opportunity and address the challenges of a restricted labor market at the same time.

 

Find out how and why so many manufacturers are turning to Augmentir to turn their workers into efficient, productive, and long-term assets for their businesses.

Check out our latest webinar – Smart Digitization of Frontline Workers to learn more.