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

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

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

augmented connected workforce acwf manufacturing

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

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

Implementing an ACWF in Manufacturing

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

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

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

Supporting Learning in the Flow of Work

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

pyramid of learning

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

ACWF tools further enhance frontline activities through:

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

augmented connected workforce in manufacturing

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

Future-proofing Manufacturing Operations with an ACWF

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

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

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

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

 

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How Skills Tracking Improves Work Allocation and Workforce Utilization

Learn how skills tracking enhances work allocation and workforce utilization to improve productivity in manufacturing.

Employee skills tracking is an excellent way to stay ahead of the curve in today’s ever-changing manufacturing landscape. Leaders can use this talent management strategy to close worker competency gaps, increase effective training, and hire qualified prospects.

Putting an emphasis on employee skills can also help manufacturers prioritize work allocation and workforce utilization. But what exactly do these two terms mean and how do they relate to tracking skills in manufacturing?

Work allocation is the process of assigning resources and roles to meet the objectives of a given task or production facility. Workforce utilization, meanwhile, refers to how a company or organization effectively utilizes its workforce to meet its operational goals and objectives.

skills tracking and workforce utilization in manufacturing

To keep up with competition, manufacturers should not only try to recruit the best possible hires, but also allocate work in an effective way to retain staff, satisfy customers, and boost profits.

Ultimately, keeping track of skills is a beneficial way to organize a company’s resources to attain sustainable business goals. Implementing a connected worker solution and digitizing skills management processes through smart manufacturing technologies is an effective way for organizations to instantly visualize the skills gaps in teams as well as track workforce skills and quickly assess both team and individual readiness.

Learn more about digital skills tracking and how it improves work allocation and workforce utilization below:

Skills tracking defined

Skills tracking helps ensure that all workers have the necessary expertise to complete tasks to their fullest potential. Basically, it closes the gap between the competencies employees already have and ones they need to further develop.

Every manufacturing firm has a unique set of job requirements and expectations. Tracking worker skills on a regular basis helps a company identify training needs and build workers’ knowledge so that they can meet expected targets. Skills management and tracking software help manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.

skills tracking software

In a nutshell, measuring employee proficiencies can boost retention, decrease the amount of time spent on tasks, and improve overall productivity.

Benefits of tracking skills to improve work allocation

Through digitization and effective skills tracking, manufacturing firms can best allocate work to team members based on expertise, credentials, and actual ability. For example, an operator who has more than 10 years of experience using computer-controlled equipment may be a better fit to handle complex machinery than an entry-level worker who lacks that training.

Additionally, with a centralized digital repository managers have a better idea of each employee’s current skills level and potential areas of improvement. Then they can close any skill gaps through training opportunities. In return, workers who receive the necessary training are more likely to thrive in their roles and be productive.

In summary, measuring worker skills can help improve work allocation by:

  • Hiring or assigning current employees to the correct jobs and tasks
  • Facilitating worker development through mentorship and training
  • Retaining high-quality employees

How tracking skills boosts workforce utilization

Workforce utilization refers to how much of an employee’s time is devoted to billable work. Tracking skills can improve this, in turn boosting productivity and profits.

When you measure how efficiently employees are doing their jobs and how well a business manages its resources, you can assure that tasks are done well and see continuous increase in revenue. Think about how many hours of each staff member’s workweek need to be billable to remain profitable and whether they are on track. With a digitized tracking system, manufacturers are able to automate and streamline this process reducing errors, improving productivity, and ensuring success.

Pro Tip

Through the use of smart, connected worker solutions and AI-based workforce insights organizations can deliver continuous, on-the-job learning based on skill tracking and real job performance, promoting reskilling and upskilling efforts enterprise wide.

To summarize, tracking skills can help enhance workforce utilization by:

  • Setting profitable rates for services based on worker output and time billed
  • Compensating employees fairly
  • Gauging whether staff is being overworked or underutilized

By digitizing these tracking processes and implementing AI-driven support, organizations can also visualize, track and offset employee 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.

Ways to track workforce skills

Tracking employee skills is a great way to improve worker performance and productivity by matching the right person with the right assignment.

One way to track an employee’s skills is through a skills matrix, which is a grid that maps staff credentials and qualifications. A skills matrix helps managers strategize and oversee current and wanted skills for a team, position, department, and more. A skills matrix is usually managed using a spreadsheet, but there are alternatives to skill matrices. For example, cloud-based skills management software can help identify and track employee competence and correlate it with actual job performance. The software can also help managers filter employee databases by skills to assemble teams or assign work based on specific qualifications.

skills matrix

Leadership can also track competencies through a skills taxonomy. Taxonomies help classify and organize skills into groups to better understand which skills employees have and which they should learn. Essentially, these structured lists help management identify and track skills to better allocate resources and worker training opportunities.

Lastly, a skills-tracking application can include AI-based software to identify and measure worker expertise and actual job performance. This is an excellent method for intelligently assigning work through skills mapping, optimizing training programs, and more. With AI-based insights and connected worker technology, organizations can bridge the gap between the training room and the shop floor, integrating training into the flow of work and creating an environment of continuous learning.

Skills management with Augmentir

Augmentir offers top-notch solutions to easily track and manage your frontline’s skillset. Our connected worker solution provides customized dashboards to streamline processes to improve workforce management, skills management, and deliver in-line training and support at the point of work, closing skills gaps at the moment of need.

If you are interested in learning how Augmentir can help improve your skills management, skills tracking, and workforce development – request a live demo.

 

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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.

The Great Resignation in Manufacturing

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

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

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

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

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

The Augmented, Flexible Workforce of the Future

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

What does this mean?

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

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

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

 

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