Posts

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

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.

Augmentir Recognized in 4 Gartner Hype Cycles for Digital Transformation and Connected Worker Innovation in Manufacturing

August 13, 2021

 

Augmentir was recently recognized by Gartner in four separate Hype Cycle reports that cover technology innovation in manufacturing. These four reports include:

  • Hype Cycle for Manufacturing Digital Transformation and Innovation, 2021
  • Hype Cycle for Manufacturing Operations Strategy, 2021
  • Hype Cycle for Manufacturing Digital Optimization and Modernization, 2021
  • Hype Cycle for Frontline Worker Technologies, 2021

In these reports, Gartner highlights Augmentir as a key software vendor in the Connected Factory Worker and Immersive Experiences in Manufacturing Operations categories.

  • Connected Factory Worker: Connected factory workers use various digital tools to improve the safety, quality, and productivity of the jobs they perform. This technology helps connect workers to the “digital fabric” of the business, providing insight into the tasks they perform so that they can be optimized and continually improved on.
  • Immersive Experiences in Manufacturing Operations: According to Gartner, immersive experiences refer to enabling the perception of being physically present in a nonphysical world or enriching people’s presence in the physical world with content from the virtual world. Gartner sees using immersive experiences for quality and maintenance tasks, remotely connecting and collaborating with employees that are not able to be on-site, or wearables for safety management.

These hype cycle reports and innovation profiles are provided by Gartner to help organizations decide which new innovations and technology to adopt, as well as what value they can provide to their manufacturing operations.

Digital Transformation in Manufacturing

According to Gartner, the manufacturing industry is being transformed by new business models and strategic, innovative technologies that fit within Industrie 4.0. Manufacturers can capitalize on advancements made in artificial intelligence (AI), visualization, collaboration, and greater connectivity across enterprises.

This was the focus in Gartner’s recently published reports, which revealed opportunities for manufacturing leaders to gain business advantages through concepts and technologies that improve productivity and decision making. Besides adding value to manufacturing businesses, they increase windows of competitive advantage.

The Connected Worker – A first step for Digital Transformation in Manufacturing

Manufacturers are beginning to recognize just how integral frontline workers are to their company’s digital fabric and that overlooking these workers has caused their digital transformation efforts to fall short of their objectives.

These same industry leaders are now investing in an integrated approach – empowering their frontline teams with connected worker solutions that utilize technology such as mobile and wearable devices, augmented and mixed reality (AR/MR), remote collaboration tools, and artificial intelligence (AI). Connected worker solutions that bring together these technologies are helping to connect a new class of workers and are allowing organizations to proactively and continually deliver the right level of training, support, guidance, and improvement.

Optimizing Worker Performance with AI

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 productivity, quality, and workforce development, setting the stage to address the needs of a constantly changing workforce.

Our view at Augmentir is that the purpose of a connected worker platform isn’t simply to deliver instructions and remote support to a frontline worker, but rather to continually optimize the performance of the connected worker ecosystem. Artificial intelligence is uniquely able to address the fundamental macrotrends of skills variability and the loss of tribal knowledge in the workforce, and creates a foundation for data-driven improvements to operational performance and continuous improvement.

“AI will play a critical role in the long-term success of connected factory workers. As more information is curated and made available, algorithms must be continually trained in alignment with continuous improvement initiatives, creating the potential for enhanced root cause analysis.”

Gartner

With an ecosystem of content authors, frontline workers, subject matter experts, operations managers, continuous improvement engineers, and quality specialists, there are dozens of opportunities to improve performance using AI. For example, after Augmentir is deployed for a number of months, our AI engine will start identifying patterns in the data that will allow you to focus your efforts on the areas that have the biggest customer satisfaction, productivity, and workforce development opportunities. This will allow you to answer questions such as:

  • Where should I invest to get the biggest improvement in operational performance?
  • What manufacturing tasks have the largest productivity or quality opportunity?
  • Where would targeted training give me the biggest return?

Augmentir’s AI continuously updates its insights to enable companies to focus on their largest areas of opportunity, enabling you to deliver year over year improvements in key operational metrics.

Interested in learning more?

If you’d like to learn more about Augmentir and see how our AI-Powered connected worker platform improves safety, quality, and productivity across your workforce, schedule a demo with one of our product experts.

 

3 Ways Manufacturers are Using Technology to Train, Develop, and Retain Talent

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.

Digital Transformation and The Cost of Doing Nothing

Prior to Augmentir, our founding team was involved in founding Wonderware Software in 1987, Lighthammer in 1997, and ThingWorx in 2008. In 2017, we recognized that the technology and market forces were aligned yet again, for a fourth industrial software revolution. A revolution that focused on increasing the productivity and quality of processes involving front-line workers.

Times have changed since 1985 when relying on tribal knowledge was the only option for a frontline worker, and today, via digital transformation efforts, we are lucky enough to have new technologies and resources that enable frontline workers to do their best work in a complex world. Although taking the steps toward digital transformation can seem scary or overwhelming, the longer you wait and “do nothing”, the more difficult it becomes to modernize. Not having the proper resources or being unsure about the digital transformation process are common hesitations for most organizations.

Beginning your digital transformation is like beginning your journey to the gym after a long day. You can come up with a million excuses for not wanting to get your workout and usually, the hardest part is actually taking the first step to get there. But once you’ve started, you never regret it! According to LNS Research, most manufacturing companies have at least begun their digital transformation journey, and for those that have not, the hardest part is just taking the first step.

Here’s what doing nothing is costing you today.

“Doing nothing” is costing you $234,900 every year with 1 changeover

If you could reduce variability in the execution of one changeover you could save 15,660 hours each year.

If the variability in completing a changeover between 2 operators is 1 hour and a changeover is performed 1/day, you are losing 261 hours each year for 1 operator.

Now, let’s look at shifts – if the average variability between A-shift, and B-Shift is +1 hour and C-Shift is +2 hours – with a total of 20 frontline workers on each shift and each operator performing 1 changeover /day the variability in hours relative to A-Shift is equal to 60 hours every day and 15,660 hours each year.

Multiply that times at the national average of $15/technician, over the course of 1 year, “doing nothing” for just 1 task is costing you $234,900 in employee time alone.

Quantify increased throughput, proficiency, productivity, and quality though frontline digital transformation, and there is even more impact!

“Doing Nothing” for manual data entry is costing you $97,875 per year

If you could save 15 minutes per day for an operator by eliminating data entry, after 1 year you would save your employee 3,915 minutes!

Multiply that time across 100 employees at the national average of $15/technician, “doing nothing” is costing you $97,875 per year.

“Doing Nothing” for apprenticeship programs is costing you $5,742,00

The average time for a new unskilled hire in an apprenticeship program is 2 years. If you could reduce the time that the new hire spends in the apprenticeship by 25%, you would save 1,044 hours for each new worker you hire. Reducing apprenticeship time by 50% would save 2,088 hours for each new hire. Reducing apprenticeship by 50% for 50 unskilled new hires would save you 208,800 hours.

Multiplying that time at the national average of $15/hour across 50 new hires, “doing nothing” to reduce a 2 year apprenticeship program by 50% is costing you $1,566,000.

Quantifying the impact on the skilled workers giving their time to the apprenticeship program, at $40/hour across 50 new hires amounts to an additional $4,176,000.

Why not start today?

If increasing proficiency can pave the way towards frontline worker digital transformation and save you the cost of doing nothing, why wouldn’t you start today?

If reducing variability can pave the way towards frontline worker digital transformation and save you the cost of doing nothing, why wouldn’t you start today?

If one simple digital procedure can pave the way towards frontline worker digital transformation and save you the cost of doing nothing, why wouldn’t you start today?

The business impacts of doing something are clear:

  • Accurate Data Entry
  • Job Visibility
  • Execution variability insight
  • Downstream impact
  • Decrease downtime
  • Increase throughput
  • Reduce/ Eliminate training
  • Easily accessible documentation

With the proper AI-powered Connected Worker tools, your workers become more integrated and you gain access to a new rich source of activity, execution, and tribal data that lead to valuable insights into areas where the largest improvement opportunities exist. AI 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.

If you don’t start now, there’s always going to be something that happens in the next 6 months that will also prevent you. This was a trend that was occurring before the pandemic, but the pandemic has accelerated it greatly. There is pressure to keep up with the new normal and the faster you start the better equipped you will be. You could continue to fight this fire with a firehose and keep it at bay, but the fire isn’t going away until you solve the root problem.

You have an opportunity, right now! Older workers are aging out, and you’re working hard to hire new, young, bright, excited workers. These younger workers expect tech. They’ll embrace change. If not now, when?

National Roots Day – A History of Manufacturing Software Innovation

Prior to Augmentir, our founding team was involved in founding Wonderware Software in 1987, Lighthammer in 1997, and ThingWorx in 2008. In 2017, we recognized that the technology and market forces were aligned yet again, for a fourth industrial software revolution. A revolution that focused on increasing the productivity and quality of processes involving front-line workers.

National Roots Day is celebrated on December 23rd as a chance to celebrate one’s history, heritage, and ancestry. It’s often said that a combination of each person on one’s family tree helps to shape them into the person they are today.

At Augmentir, we agree that the past is important, and it has definitely shaped Augmentir into the company it is today. This year, we’re using National Roots Day to reflect on our history and how Augmentir came to be the modern Connected Worker platform that you use and trust today. The Augmentir founding team, Russ Fadel, Phil Huber, and Lawrence Fan, has been at the forefront of the most important software technology revolutions. Prior to Augmentir, our founding team was involved in founding Wonderware Software in 1987, Lighthammer in 1997, and ThingWorx in 2008. 

In 2017, the founders of Augmenir recognized that the technology and market forces were aligned yet again, for a fourth industrial software revolution. A revolution that focused on increasing the productivity and quality of processes involving front-line workers. 

Transforming How Machines Run

In 1987, Wonderware transformed how machines run, with the introduction and mass commercialization of Human-Machine Interface software. Wonderware enabled the first software-based industrial revolution and is still in evidence today by Wonderware’s continued leadership position.

Revolutionizing the Factory Floor

In 1997, Lighthammer transformed manufacturing yet again with the introduction of the first Enterprise Manufacturing Intelligence platform. Lighthammer revolutionized the factory floor by bringing both real-time intelligence and live synchronization with the ERP software layer. This enabled the second software-based industrial revolution and is still evidenced today by the ubiquity of this software (currently under the SAP MII brand).

Catalyzing the Industrial Internet of Things (IIoT)

In 2008, ThingWorx catalyzed the Industrial Internet of Things (IIoT) with the introduction of the first application platform for IIoT. ThingWorx transformed both manufacturing and service, becoming synonymous with Industrie 4.0/Brilliant factory, and Connected Service. This enabled the 3rd software-based industrial revolution and is still evidenced today by the ubiquity of IIoT software and the market leadership of PTC’s ThingWorx brand.

 

Today, at Augmentir, we are continuing this trend of bringing innovative software into the manufacturing sector by focusing on the people that make up such an integral part of the digital transformation equation.

The Human Side of AI: Supporting Workers to Reduce Employee Burnout

AI and connected worker technology is helping frontline managers combat employee burnout and improve engagement and retention.

Industrial work comes with an immense amount of stress. Without providing the worker with the right level of support, this stress can lead to increased errors, poor work performance, and eventually, employee burnout. Recently, Gallup reported that 76% of employees experience some form of workplace burnout. This not only affects performance and productivity but much more, including engagement and employee retention.

employee burnout

To offset employee burnout, managers should aim to:

  • Reduce employee stress
  • Remove roadblocks ensuring their workers have the proper tools to complete their tasks
  • Ensure workers are a good match skill-wise for the work they are doing
  • Give workers a say in how the work is completed
  • Empower workers to believe that the work they are doing is valued and important

road to flow

In a 2022 Gallup poll, 79% of employees responded as not being engaged at work, this same poll found that most employees don’t find their work meaningful and do not feel hopeful about their careers.

When supporting workers and battling workplace burnout, there is no “one size fits all” answer, and many organizations are realizing that taking the same approach for “desk workers” does not account for the many and uniquely different needs demanded by frontline or “deskless” workers. Managers must keep in mind these needs when combating and detecting burnout and boosting employee engagement.

Artificial Intelligence (AI) and machine learning-based technology combined with a worker-centric approach can help tremendously in this respect, accounting for the human element in industrial operations while still taking advantage of innovations.

Using AI to Enhance Worker Experience and Reduce Burnout

By utilizing the capabilities of connected worker platforms and AI, companies can take a proactive approach to reducing stress and preventing employee burnout.

The meteoric rise of AI tools like ChatGPT and natural language processing has created a surge in interest in all things AI and while it’s not a cure-all, AI has the potential to be extremely effective in helping workers get access to the information and support they need while on the job, as well as predicting, detecting, and reducing workplace burnout. By taking highly granular connected worker data and using AI to filter out the unnecessary portions, industrial operations are able to not only improve tasks and productivity but better support and empower frontline workers. Organizations can use AI to engage employees by:

  • Creating communication touchpoints and streamlining communication
  • Pairing workers and tasks based on skill level
  • Suggesting training and certification opportunities for upskilling workers
  • Create feedback paths so employees have a say in how tasks are completed

To complement AI and software platforms, organizations can implement other tools such as wearable devices, mental health applications, and more to aid in engagement efforts. Finding the right balance and combination is key for knowledge exchange and conversation – making employees more engaged within the team.

The Human Element

It is important to take advantage of new technologies and implement them where needed, but technology by itself is not the answer. Finding a balance between technology integration and a worker-driven approach is key and it is paramount that the true needs of the workforce are not forgotten. Although AI and machine learning-based technology can help tremendously with detecting and reducing employee burnout, it has its limits and can only do so much. Technology cannot replace how workers feel and how they interact with management on a day-to-day basis. And at the end of the day, AI can only augment employees and should be used to empower them, never to replace them.

Darwin in Manufacturing: The Evolution of Connected Worker Software

Connected frontline operations platforms are helping manufacturers reduce downtime and provide a foundation for a holistic preventive maintenance strategy.

Beginning in mid-2022 and now increasing in 2023, there is a significant trend of companies moving away from earlier investments in connected worker software tools to Augmentir’s Connected Worker Platform.

Early adopters and pioneers of V1.0 connected worker tools and technology deserve respect for leading the charge into Industry 4.0 and the concept of a connected workforce. However, we also admire those leaders who realized there are more transformations and improvements to make – such as value in the data from your connected workers and incorporating AI-driven solutions to make sense of that data. These innovative leaders dared to adapt, continue innovating, and replace the connected worker software systems that were not solving enough of the challenges faced by the modern workplace.

darwin in manufacturing

By combining AI-powered software and smart connected worker solutions, manufacturers are able to get next-level results and improve frontline worker productivity, engagement, and safety.

Following in the Footsteps of Industrial Transformation Leaders

According to LNS Research (a leading analyst firm in defining the connected worker space), the business case for connected worker software continues to grow, and solutions that incorporate emerging technologies like AI are leading the way. In fact, LNS states that Industrial Transformation Leaders (IX Leaders) are two times more likely to use AI-enabled advanced analytics capabilities. These leading manufacturers are supporting their frontline operations with AI-based technology for training and skills development, real-time worker performance support, and providing dynamic and personalized content.

Here at Augmentir, we have seen quite a few companies that fall into the category of the courageous, understanding that they needed to continue adapting for their business to thrive.

We have been honored to be recently chosen by several global leaders as their connected worker V2.0 solution, including:

  • one of the largest paint manufacturers in the world
  • one of the largest agricultural companies in the world
  • one of the largest food manufacturers in the world
  • one of the largest manufacturers of batteries in the world

All of these world leaders recognized that their current connected worker software solutions had become insufficient and that they needed a smarter, more complete solution to help them overcome their frontline workforce challenges and current business obstacles.

Here are three key takeaways you can use from these companies that went back to select a new connected worker solution:

  1. Don’t be afraid to make a change that will have a positive impact on your business, even if you are the one who made the initial decision.
  2. If you have experience choosing early connected worker tools, build on that experience. You are ideally situated to identify gaps in processes and improvement needs; and know best which tools to use to address the overall operational needs of the business.
  3. Use your prior experiences to build processes for re-evaluating connected worker solutions from the perspective of already experiencing one fully deployed.

In one example, a global manufacturer invested in an early connected work tool and had been using the tech for nearly 4 years. However, once they decided they needed a new solution, they then went back to evaluate the market for the right tool. They made a list of selection criteria they knew they wanted from this new solution, from that they looked at approximately fifteen (15) connected worker vendors, and from there they narrowed down to the three (3) they ended up testing. They even included having a couple of integrations in their POC as they knew that an integration into their ERP, Quality Management, and Asset Management systems was something they needed, and they had poor experiences previously with vendors overcommitting.

Pro Tip

We suggest anyone evaluating a technology use this same approach – include integrations as part of your Proof-of-Concept to ensure that you are not getting hypothetical answers to hypothetical questions, and that the solution meets your true business needs.

What our customers tell us

Here is what customers are telling us they are looking for in a V2.0 connected worker solution, and the reasons they changed to Augmentir’s Connected Worker Platform:

  1. Ease of Use: Augmentir prioritizes a user-friendly experience. Its intuitive interface and workflow builder makes it easy for employees to adopt and use the tool effectively. This can result in faster onboarding and increased overall productivity.
  2. Augmented, Personalized Work Instructions: Augmentir provides a workflow and content creation environment that allows you to digitize standardized work instructions, and adjust content and in-line training to suit the needs of individual workers.  This optimizes performance and speeds up onboarding time for new employees.
  3. Upskilling and Reskilling: Augmentir’s ability to deliver formal skills and learning in the flow of work means a worker can stay current in their needs, continue to grow in their role, and build a structured career path within their company. This approach appears to be driving increased retention and job satisfaction.
  4. Workforce Optimization: Augmentir’s ability to assess in real time who is available to work on any given day and then balance the skill level best suited for a task with the available workforce offers optimal productivity based upon what you have to work with on any given day.
  5. Digitizing Complex Workflows: Most solutions on the market allow you to digitize simple workflows. With Augmentir, manufacturers can build complex workflows that satisfy use cases that are unique to their business, and extend those workflows to support greater integration into their business processes.
  6. Industrial Collaboration: Augmentir enables remote collaboration among workers and experts. This functionality is particularly useful when experts are not physically present at the job site. Remote experts can guide workers through AR annotations and audio/video communication, fostering knowledge sharing and faster problem resolution.
  7. Continuous Improvement: Augmentir focuses on driving continuous improvement within organizations. It leverages AI to analyze data from worker interactions and identifies areas for improvement. This data-driven approach allows companies to optimize processes, increase productivity, and reduce costs over time.
  8. Integration and Scalability: Augmentir offers integration capabilities with existing enterprise systems, such as enterprise resource planning (ERP) or manufacturing execution systems (MES). This ensures seamless data exchange and workflow integration. Additionally, Augmentir is designed to scale with the organization’s needs, accommodating both small teams and large enterprises.
  9. Analytics and Insights: Augmentir provides robust analytics and reporting features driven by AI-powered solutions and focuses on AI as a core component of Connected Worker V2.0. This allows managers and supervisors to gain valuable insights into worker performance, task completion times, and areas that may require additional training or support. Data-driven analytics can aid in identifying bottlenecks, optimizing processes, and making informed business decisions.
  10. Customization and Flexibility: Augmentir allows organizations to customize their work instructions and workflows to fit their specific needs. This flexibility enables the tool to adapt to different industries, processes, and work environments.

 

If you are interested in learning for yourself why companies are choosing to change to Augmentir over their current connected worker solution – reach out to book a demo.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

Using AI to Operationalize Training for Manufacturers

AI and connected worker technology is helping frontline managers combat employee burnout and improve engagement and retention.

In today’s fast-paced manufacturing industry, staying ahead of the curve is critical to success. To remain competitive, companies must continuously reskill and upskill their workforce. One way to achieve this is to operationalize training and bring it closer to the factory floor using artificial intelligence (AI) and connected worker technology. Operationalizing training means taking a more systematic approach to training and workforce development, rather than treating it as a one-time event.

operationalizing learning

According to a report by McKinsey, companies that embrace AI-powered learning reduced training time by up to 50% and improved learning outcomes by up to 60%.

AI-powered solutions make learning more accessible, engaging, and effective; and by integrating training and learning solutions into the everyday operations of the company, manufacturers can create a culture of continuous learning and improvement. In fact, here at Augmentir we’ve seen manufacturing companies use this approach to reduce new-hire onboarding and training time by up to 72%.

Learning: When and Where it’s Needed

AI has the potential to revolutionize many industries, and manufacturing is no exception. Many workers in the manufacturing industry work in shift-based environments, making it difficult for them to attend traditional classroom-based training sessions.

With AI, organizations can incorporate more learning processes into the everyday workday of frontline workers – essentially operationalizing training and 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 (or workflow 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.

This approach 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 customized to each worker’s skill level, making it easier for them to learn at their own pace.

Additionally, AI-driven learning solutions offer:

  • Personalized Learning: AI-powered learning solutions can be customized to each worker’s skill level, making it easier for them to not only learn at their own pace, but also matched to their experience level. For example, novice workers may be required to watch a micro-learning video as a safety prerequisite to performing a task, whereas a more senior worker with the appropriate level of job experience and proficiency may not be required to watch the learning video.
  • Performance-based Learning: AI-powered solutions provide workers with hands-on learning experiences that are customized based on their actual job performance. These experiences can be delivered through a variety of content mediums – rich media, self-help guides, microlearning videos, and even augmented reality (AR) experiences.
  • Real-Time Feedback: AI-powered solutions can monitor worker performance in real-time, providing instant feedback to help workers improve to provide access to content to help resolve issues in the flow of work.

AI can also help with the assessment of employee performance. Traditional performance evaluations often rely on subjective assessments from managers. Conversely, AI-powered performance evaluations can provide a more objective and data-driven assessment of employee performance, while also providing a more accurate picture of an employee’s strengths and weaknesses.

Better Training, Better Work

By implementing AI-based solutions, companies can identify and operationalize training needs across the organization. Using performance data, AI can uncover gaps in knowledge or skills across the workforce, which can then be used to develop targeted training programs to “fill” these gaps.

Once implemented, AI can be used to effectively track and improve learning and training effectiveness, leveraging data on worker performance before and after training to measure impact and refine training programs to ensure that they are delivering the best outcome.

As the manufacturing industry continues to evolve, so must how they approach learning solutions. A recent Deloitte survey found that over 90% of companies believe that AI-powered learning will be important for their organization’s success in the next three years. AI has the potential to operationalize training and transform learning in the manufacturing industry by bringing it closer to the factory floor. By leveraging AI-powered personalized learning, real-time feedback, data-driven performance evaluations, and identifying training needs, industrial organizations can create a more efficient, effective workforce.