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.

Why You Should Be Thankful For AI in Manufacturing This Year

Being thankful for AI might not seem like one of the usual items to include on your “What I’m Thankful For” list, but, AI truly has laid the foundation for not only the Augmentir platform, but for transforming the manufacturing workforce in positive ways

Every year as Thanksgiving approaches in the United States, we take time to reflect on what we are thankful for in our personal lives, such as family, friends, and health to name a few. As we started thinking about what we’re thankful for from a work perspective here at Augmentir, many things came to mind: our wonderful clients, an awesome team, our incredible founders, but one item high on our list is something that has allowed us to stand out in the Connected Worker platform space and make our product what it is today – Artificial Intelligence. Specifically AI in manufacturing. 

Being thankful for AI might not seem like one of the usual items to include on your “What I’m Thankful For” list, but, AI in manufacturing truly has laid the foundation for not only the Augmentir platform, but for transforming the workforce in positive ways as you’ll see below.

Improved Safety in the Workplace

One of the most common use cases for adopting AI has been in workplace screening and safety primarily as a result of the pandemic. Manufacturers found use in AI to monitor interactions of employees that needed to be in person on the shop floor during the pandemic so that they could conduct contact tracing and facility sanitization if necessary. Seeing the value of AI in workplace safety, manufacturers have continued to implement AI strategies for long-term solutions to identify safety events before they happen or to speed up post-incident root cause analysis for accidents like trips and falls. Industrial companies that implement AI-powered connected worker solutions as part of their digital transformation strategy have seen up to an 80% decrease in reportable injuries.

Connecting the Frontline Worker

According to Cisco, there are over 3 billion workers across the globe, and nearly two-thirds of these workers are frontline or field workers, whose day-to-day duties require that they physically show up to their jobs. Over the years, the manufacturing industry has done a really good job of connecting machines in the fabric of the business and giving operators the necessary data to help run those machines better. Our frontline workers 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 have access to the data that they need, when they need it. AI-powered connected worker tools provide not only a path to connect workers, but also intelligently deliver the right level of performance support so they can perform at their best.

Making Sense of Valuable Data

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. AI algorithms in manufacturing are ideal for analyzing large amounts of data collected from a connected workforce. AI can detect patterns, find outliers, cleanse data and find correlations and patterns that can be used to identify opportunities for improvement and create a data-driven environment that supports continuous learning and performance support. Using AI insights derived from Augmentir’s Connected Worker Platform, Colgate-Palmolive was able to save 10-30 minutes saved per shift and as much as 120 minutes reduced between Maintenance Notification and Maintenance Order Closure (Maintenance Execution Time).

Continuous Learning & Development

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. Implementing AI in manufacturing training 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 on-demand 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.

 

At Augmentir we believe that the purpose of a Connected Worker platform isn’t simply to deliver digital work instructions and remote support to a frontline worker, but rather to continually optimize the performance of the connected worker ecosystem. AI is uniquely able to address the fundamental macrotrends of skills variability and the loss of tribal knowledge in the workforce. 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 – and that’s something to be thankful for.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, check out our latest eBook – Build a Modern, Connected Workforce with AI.

How Digital Transformation Shapes the Future of Food Manufacturing

These virtual events were a great way to connect with manufacturing professionals and discuss some of the industry’s top challenges and topics – workforce transformation, learning and development, lean manufacturing, and autonomous maintenance.

Last week, Augmentir participated as a sponsor in the 2021 American Food Manufacturing Summit. This 3-day virtual event was designed to bring food and beverage manufacturers together to discuss current trends, strategic insights, and best practices in an ever-evolving environment. The event focused on addressing today’s top challenges and future of food processing and manufacturing, specifically around embracing digital transformation and technology for manufacturing excellence. Attendees were able to connect with top industry influencers and learn about different strategies to improve automation, operational excellence, quality, and safety in the food manufacturing industry through open roundtables and 1:1 meetings.

Augmentir’s Enablement Director, Shannon Bennett, hosted an open roundtable discussion on the role digital transformation plays in food and beverage manufacturing, and how technologies like artificial intelligence (AI) and connected worker platforms are helping companies kick-start their digital transformation efforts. During the discussion, Shannon opened the floor to the attendees to discuss the day-to-day challenges they face at their manufacturing organizations and the tools they’re looking into to solve those challenges. 

Solving Manufacturing’s Biggest Challenges with AI and Connected Worker Technology

The roundtable consisted of executives and manufacturing leaders from some of the world’s largest food and beverage companies to smaller family-owned and operated specialty food and beverage manufacturers. Throughout the roundtable, we heard the same challenges and frustrations related to standardization, moving from paper to digital processes, data collection, lack of traceability, and an overall need for digital transformation.

The overarching roundtable discussion was around digital transformation. Food and beverage manufacturers are accelerating the pace of digitization to address their top challenges – the labor crisis, increasing skills gap, and increased pressure for improved production efficiency, changes in consumer demands, and increased regulatory compliance related to food safety.

Moving from Paper to Digital

During our roundtable discussion, most of the manufacturing leaders were in the discovery phase of their modernizing process, where they were beginning to look into digital solutions to solve their challenges around manual processes and efforts to reduce paper. Some of the discussion around paper included issues with quality on the shop floor and wanting to go paperless, easier access to training for employees, lack of traceability (for example, maintenance schedules need more visibility of completion, where issues arise, and more transparency all around), and digitizing information from a quality standpoint.

Digital work instructions reduce the need for paper and deliver information to frontline workers when and where they need it. This provides frontline workers with a standardized way of performing technical work.

Lack of Data-Driven Insights into the Work Being Done

Another key challenge was the lack of insight into how workers were performing their jobs – whether it be in quality, equipment operation, or maintenance. One participant discussed labor challenges in their organization and that when they collect data it often gets lost and when they come back to it, they don’t know or remember why they’ve collected it in the first place.

Connecting workers with digital tools is merely a first step in the process of truly understanding and getting clarity on the work being done. Connected Worker data is inherently noisy, generating misleading signals that traditional business intelligence (BI) tools aren’t designed to handle. This leads to murky or contradictory conclusions that prevent organizations from taking anything but a “one size fits all” approach to work process and workforce investments. Or, even worse, false conclusions are generated about the state of work process and workforce opportunities, leading to targeted investments into the wrong areas.

The discussion shifted to AI as a solution not only bringing clarity to the work being done, but also more generally democratization of the workplace, and giving employees the tools to use data effectively to improve manufacturing operations. AI is designed for purpose to recognize patterns in the noisy data sets generated by a factory workforce, letting your continuous improvement and operations teams focus on what’s really going on.

Training

Employee onboarding and training was also a hot topic of discussion. Many participants spoke about manual processes and how traditional training methods are proving to be ineffective.  Traditionally, there was a clear separation between training and work execution. However, many participants shared that they are starting to re-think how they are training and onboarding their workers, and shifting more towards delivering training at the moment of need. The roundtable participants discussed at length approaches and strategies for re-thinking how training is delivered for today’s workforce.

Build a Modern, Connected Workforce with AI

To address these challenges, the roundtable participants overwhelmingly agreed that digital transformation initiatives for food manufacturing should start by focusing on streamlining data collection and digitizing valuable data. Using an AI-powered connected worker platform to accelerate this effort not only furthers a company’s digital transformation efforts, but also provides a whole new set of data that can provide really interesting insights and optimization opportunities. AI doesn’t remove the human worker from the equation, but rather, takes the human worker and embeds them into the digital operation.

 

To learn more about how AI is being used to digitize and modernize manufacturing operations, check out our latest eBook – Build a Modern, Connected Workforce with AI.

 

AI Manufacturing 2021 – Event Recap

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November and discuss how AI is shaping the future of the manufacturing workforce.

After more than a year of virtual conferences, we were finally able to participate in person at the AI Manufacturing conference in Dallas early this November. This year’s event was hybrid, face-to-face on November 3 and 4th, and virtually on November 5th. While it was refreshing to be able to network face to face with leaders in the Manufacturing industry, it was great to have the opportunity to also network virtually on November 5th. If you aren’t familiar with the AI Manufacturing conference, this conference is the leading Artificial Intelligence event for Manufacturing Industries. This year’s event focused on:

  • The use of AI to Improve Quality, Reduce Defects, and Increase Profits
  • Developing a Digital Twin to Optimize Plant Operations
  • Using Building Blocks to Modernize Manufacturing Activities and Facilitate Growth
  • Designing  Products Enabled by Additive and Hybrid Manufacturing Techniques
  • Exploring the Use of AI in Industrial Attacks and Defense

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

Dave Landreth, Augmentir’s Head of Customer Strategy had the opportunity to present on “Using AI to Unlock to the True Potential of Today’s Connected Workforce”. In this session, he discussed the variability of the workforce with generations, how they need to be trained differently, and how AI can assist in worker proficiency. Dave also discussed Bob Mosher’s 5 moments of need and how AI can be applied at the time of learning. 

The Misunderstood Fear of AI

Our founders saw that the humanistic approach was missing with traditional connected worker platforms and realized that AI was the key to saving the manufacturing world and unlocking worker potential. However, companies are reluctant to adopt AI in fear that automation will take over and eventually replace human workers in manufacturing. Others fear that AI would be used negatively to track workers, in a “big brother” type of way.  

As we’ve seen with our customers, this couldn’t be farther from the truth. When AI is leveraged ethically with the workforce in mind, it can be used to help improve and ultimately grow the talent of your workers. Assessing workers on their performance has been done for years through subjective performance reviews. Using AI allows the assessments to be based on data and can provide a path forward for worker improvement and continued growth. 

Understanding Today’s Struggles Within Manufacturing

Manufacturing workforce challenges

The struggles that manufacturers face today aren’t the same struggles that were present 40 years ago. One of the number one issues in manufacturing is hiring. Today, most manufacturers believe that hiring is a risk, with a limited pool of candidates. They are struggling with employees who don’t have the needed skill set and are questioning how they can train them and evaluate their performance. 

Manufacturing companies also struggle with retaining employees. We are all aware of the workforce retention issues right now. Employees are feeling like they aren’t heard and that they can’t contribute to the company, which causes them to look for a new career. There is also the struggle of thoughtful upskilling, meaning that formal training programs only recognize one type of worker. The average manufacturing plant sees 4 generations of workers, ranging from those fresh out of high school to the ones that have worked on a plant floor for 40+ years. Different generations learn differently and require different levels of support. There isn’t a one size fits all approach for teaching different generations. 

Another challenge with the workforce that isn’t as obvious, is with mergers and acquisitions. An acquisition means that companies now consist of two workforces doing things differently and needing to understand what part of procedures from the newly acquired company is worth incorporating into the existing procedures.

Leveraging AI to Help Build and Grow a Top Performing Workforce

Build and grow a top performing manufacturing workforce

AI is uniquely suited to solve these challenges, and we recognized that early on at Augmentir. We started looking at how AI could help build and grow a top performing workforce. One way AI can help is the ability to hire for potential by increasing the hiring of candidates to those not as skilled. AI allows companies to understand a worker’s skillset and provides the ability for personalized workflows to guide them in the context of work while they are doing their job, whether it’s a new worker or one with dozens of years of experience. AI can also help with the “Right person – Right Job – Right Time” approach – always ensuring that the correct person is performing the task at the most efficient time. 

The use of AI allows all workers to contribute by allowing inline feedback to optimize work procedures. In addition, AI can be used to ensure personalized career job competency allows workers to be hired even if they do not have the optimal set of skills and experience. Measuring a worker’s proficiency when they are completing the work allows the worker to focus on each specific step and guides them at the time of need, instead of during classroom training. AI provides workers with predictive and stable data to help them grow in their roles. Having a data-driven way to measure success and provide advancement opportunities helps establish career paths as well as opportunities to grow. 

With an AI-based onboarding approach, organizations are able to hire a wider range of individuals with varying skill sets. If we can teach someone in the context of doing their work, onboarding time is reduced due to being able to train them in the field. We also see an increase in productivity and are constantly evolving their learnings. When workers feel included and confident about their careers, they are also more likely to want to stay and grow with the company. The ability to train workers in the field while doing their jobs with AI personalization allows you to clearly and quickly assess how a worker is doing, where you focus the help to them, and driving those 1:1 work procedures is a game-changer.

AI in Manufacturing will solve many of the challenges that we are seeing. 

Learning & Development and the 5 Moments of Need

The Five Moments of Need methodology was created by Bob Mosher, a thought leader in learning and development with over 30 years of experience. He realized that after 20 years, classroom teaching was the wrong approach since it rarely teaches you things that you do in your job on the shop floor. Classroom learning allows an individual to gain a certain level of confidence, but quickly falls off when it’s time to apply it within context to a given workflow.  

According to Bob’s methodology, the 5 moments when our workforce needs knowledge and information consists of: 

  • When people are learning how to do something for the first time (New).
  • When people are expanding the breadth and depth of what they have learned (More).
  • When they need to act upon what they have learned, which includes planning what they will do, remembering what they may have forgotten, or adapting their performance to a unique situation (Apply).
  • When problems arise, or things break or don’t work the way they were intended (Solve).
  • When people need to learn a new way of doing something, which requires them to change skills that are deeply ingrained in their performance practices (Change).

The approach that Bob and his team adopted in the last 10 years is to think more about performance support. The variability of the workforce, both skilled and young, proves that there’s not a one size fits all approach. This is where AI comes in: being able to deliver personalized work procedures for every worker, allowing for continuous learning and growth. Based on proficiency, there may be a more guided set of work instructions, a session with a remote expert, or a supervisor sign-off required in order to complete the job on quality and on schedule. AI can also be used to continuously measure and assess how the workers are doing. This is where organizations can start seeing growth within their workforce.

Looking Ahead

We had a blast at this year’s AI Manufacturing conference and are already looking forward to another successful event next year! If you’re interested in learning more about why AI is an essential tool in digital transformation, from reducing costs and downtime to improving over quality and productivity, we’d highly suggest considering attending next year. In the meantime, if you’re looking for information surrounding AI, digital transformation, and building a connected workforce, check out our eBook: “Building a Modern, Connected Workforce with AI”.

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.

Skills Matrix: How to Create and What are the Alternatives?

Learn about what a skills matrix is, how these can be used and alternatives to help track employee skills.

A skills matrix is a grid that maps employees’ skills and qualifications. Companies use this information to manage, plan, and monitor current and desired skills for a position, team, department, or project.

Having a place to store each employee’s skills and experience level can help managers decide how to divvy up tasks. It’s also a great way to gauge areas of improvement.

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

To help you learn more about the skills matrix and its alternative, this article explores the following topics:

What is a skills matrix?

A skills matrix is a tool used by employers to track workers’ skills and expertise. Typically maintained in spreadsheet format, it usually includes skills that workers already possess, ones that are needed but underdeveloped, and those that are required to complete a project or perform a job function.

Each employee is given a rating on their proficiency in each skill and their interest in developing it. This gives managers great insight into who is qualified to complete certain tasks.

What are the benefits of using a matrix to track employee skills?

A skills matrix offers multiple benefits that can increase team performance and boost productivity. Some of its benefits include:

1) Brings awareness to employee skills

This tool shows what area a team member excels at and where they can improve. This can bring awareness to what skills need to be cultivated and what areas team members are already proficient in.

2) Sets team expectations

With the matrix outlining what skills are needed to complete a project, employees have a better idea of what’s expected and required to be proficient in their roles.

3) Shows where new hires are needed

The matrix gives employers a better idea if someone needs to be hired to fulfill a certain role. Knowing which skills are missing helps managers determine what kind of employee needs to be hired for a specific project.

How do I create a skills matrix?

Creating a skill matrix can provide a wealth of benefits to a business. You can set one up by following the steps below:

  1. Determine which skills are needed for your team based on job function or responsibility.
  2. Evaluate your workers’ skills and qualifications.
  3. Create a grading system to rate each employee’s current skill level.
  4. Fill in the missing criteria and manage the information in a central skills management system.

skills matrix for skills management

How can skills matrices be used in the manufacturing industry?

The manufacturing industry is always seeking skilled employees. Skilled matrices are an excellent way to cultivate the skills of current production plant workers and boost productivity.

This organizational tool also simplifies the hiring process. For example, it gives managers a better sense of what skill areas are lacking and who may be the right fit for the role.

The better equipped an employee is to do their job, the better a company’s bottom line will be.

What are the alternatives to using a spreadsheet for your skills and competency matrix?

If you’re looking for an alternative to using a spreadsheet to manage the skills of your team, consider cloud-based skills management software. These programs help businesses identify and track worker competency.

For example, this software maps skills from a centralized library to job profiles and individual employees to help managers analyze the abilities of their teams, the desired skills for each role and any skill gaps that exist. Learn more about skills management software in our guide.

Furthermore, skills management software not only allows you to efficiently manage skills for your frontline workers, it also enables you to use this skills mapping to intelligently assign work or identify upskilling or reskilling needs.
skills job proficiency mapping

 

Interested in learning how Augmentir’s connected worker platform can help you digitize and effectively manage skills within your manufacturing operation? Get in touch with us for a free demo.

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Asset Maintenance Best Practices

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

Asset maintenance refers to everything that goes into keeping your manufacturing assets in tip-top shape. With machinery, for example, asset maintenance means conducting frequent inspections and repairs. With office space, this term involves maintaining a clean, safe, and productive workplace. With products, it includes checking finished goods for any deficiencies or errors.

In a nutshell, asset maintenance helps prolong the performance and lifespan of equipment, machinery, goods, and more. Performing this strategy ensures that your essential business resources continue functioning smoothly and properly.

Learn the best practices for increasing asset maintenance performance:

Best practices for optimal asset maintenance performance

Implementing key best practices can improve asset maintenance in manufacturing. We’ve put together five crucial strategies to ensure your manufacturing firm is performing at its best while minimizing costs:

1. Gather as much info as possible

Gathering data on assets can help management make better informed production decisions. Asset tracking is a great technique to accomplish this.

2. Create a preventive maintenance schedule

The data that’s been collected will make it easier to create a preventive maintenance schedule. To create one, start by organizing asset data and analyzing the info you’ve amassed (e.g., how often each item must be checked and maintained). Lastly, prioritize your most important assets and allocate funds to maintain them.

schedule and audit asset maintenance work

3. Train workers

Investing in your employees pays off. Procedural documentation and training will help ensure that all maintenance work is thoroughly performed and recorded. Skills management software can help with ongoing management and tracking of employee skills and training requirements.

4. Apply an inventory tracking system

There is nothing worse than beginning a project only to find out that you don’t have all the moving parts to complete it. An inventory system helps reduce the chances of missing crucial product information and enables you to better track company assets.

5. Track asset maintenance key performance indicators (KPIs)

KPIs such as mean time between failures (MTBF), overall equipment effectiveness (OEE), and work order resolution time can give a performance review on how well your assets are doing. They’re also great at pinpointing which areas could benefit from predictive maintenance, the process of checking for deficiencies to avoid future machine breakdowns.

Pro Tip

Asset management software like Augmentir’s Connected Worker Solution helps you simplify the operations and maintenance of your facility. Manage work and maintenance procedures, skill requirements, training, KPIs, and preventive maintenance schedules all through a visual interface. Connected worker solutions help integrate your CMMS with your shop floor operations.

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Advantages of asset maintenance

The maintenance of assets in manufacturing consists of regularly inspecting, repairing, and replacing equipment and other assets to confirm that everything is in workable condition.

Advantages of asset maintenance:

  • Enhanced workplace safety
  • Greater equipment reliability
  • Longer machine lifespan
  • Lower maintenance costs
  • Improved productivity
  • Better regulatory compliance

Asset maintenance tools and how Augmentir can help

Manufacturers are encouraged to manage and track assets to limit product flaws, prevent machine failure, and improve overall productivity. However, in today’s digital age, especially with more mobile devices, complex cloud-based technologies, and software updates, handling assets has become much more complicated.

This is where Augmentir’s AI-powered connected worker solution, or asset management software, comes in. Our solution allows manufacturing facilities to better monitor their assets and manage them effectively with easy-to-use customizable dashboards and real-time insights.

Asset maintenance with Augmentir

Ours is the world’s only connected worker suite that provides an overarching view of an asset’s life cycle. Accurate digital asset records can help manufacturers with resource planning. In addition, our tool helps with asset record keeping so that you don’t have to worry about not meeting regulatory compliance requirements.

Though a manufacturing firm could use a spreadsheet to track its assets, our digital solution gives workers the ability to evaluate asset-specific data and make better decisions about how to manage each one.

Transform how your company runs its maintenance operations. Request a live demo today!

 

 

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The Real Benefits of Digital Work Instructions in Manufacturing

The benefits of digital work instructions go far beyond simply standardizing work. The real benefit is in personalized guidance and support for today’s workers.

Digital work instructions are step-by-step directions on the best way to complete any task, from basic maintenance to fixing equipment. These digitized instructions are electronic versions of work procedures that are kept in a centralized system so workers can easily access them to work on tasks or to make timely decisions on projects. While the benefits of digital work instructions are numerous, the real benefit in manufacturing comes when digital work instructions can be personalized to the unique needs and skills of each worker.

So say goodbye to static documentation and hello to a new era of personalized digitization. If you’re interested in learning the real benefits of digital work instructions, read on about the following:

How digital work instructions are transforming manufacturing processes

Traditional instructions on paper can slow down a manufacturing operation. They can be lengthy, become quickly outdated, and are often full of mistakes. With paper-based reporting, for example, workers may forget to note the condition of equipment or update a faulty procedure.

Fortunately, digital instructions are an ideal solution. They offer visual demonstrations, how-to videos, and other resources for completing tasks. Most importantly, when digital work instructions are managed and delivered through a connected worker solution, they can be kept up-to-date to ensure compliance and product quality. According to Quality Magazine, not only do digital work instructions support overall enterprise productivity, but they also provide workers with an improved level of control over their work through enterprise data and automated insights.

benefits of digital work instructions

When you digitize your procedures, they can be accessed and kept up to date from wherever employees work. They can be enhanced with visual aids, contextual information, and augmented reality experiences to guide workers through complex jobs. Best of all, workers are less likely to make mistakes or miss steps when they can easily refer to clear and visually engaging information.

Digital work instructions are maintained via a connected worker solution, and delivered through mobile or wearable devices on the shop floor. These solutions can be coupled with AI-powered software to further help companies digitize production procedures.

This leads to greater worker productivity and output.

The real benefits of digital work instructions

Digital work instructions provide countless advantages when implemented throughout your entire organization, including improved production processes, decreased downtime, greater operational competence and safety, as well as support for a centralized database of knowledge. On their own, they deliver standard work guidelines but fail to consider the unique skills of each worker, which is increasingly important in today’s evolving and labor-constrained workforce.  The typical one-size-fits-all approach to managing, guiding, and supporting employees won’t cut it in today’s market.

Businesses need a solution that helps them improve manufacturing processes and meet their workers where they are.

This is where AI-based solutions come in.

Using AI-based connected worker solutions, organizations can digitize and easily manage skills tracking and training programs and connect them with frontline operations. Embedded AI can dynamically optimize work processes to deliver training in the flow of work, tailored support, and more. 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. These benefits extend beyond simply standardizing work to include:

1. A more motivated, more engaged workforce

An organization’s commitment to cultivating its team’s skills can influence their attitudes toward the job. A worker is likelier to perform better when valued and appreciated. Digitized skills tracking also ensures that workers are qualified to perform their job.

2. Mitigate risk and ensure safety

Solutions that include personalized work instructions that incorporate worker skills allow organizations to validate at the time of work assignment who has the skill level to safely perform a specific task. This helps to mitigate risk and ensure safety.

3. Intelligently assigning work

Ensure the right person is assigned to the right job. Manage work assignments based on skill level, endorsements, and actual job performance.

skills taxonomy

4. Closes the skills gap

Tracking skills is a great way to identify gaps between the skills employees already have and the skills they need. With this information, the company can arrange for additional training or other ways to invest in their employees. Keep in mind that as your manufacturing organization evolves and grows, so should your employee skillset.

6. Identify upskilling or reskilling opportunities

Use data from actual work performance, combined with an employee’s current skills and endorsements to inform your reskilling and upskilling decisions. Knowing where improvements need to be made can close any learning gaps and boost the overall success of a company. Optimizing your workforce can help improve productivity in every department, giving your company a competitive edge in today’s market.

 

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.

FAQs about digital work instructions

What is the purpose of digital work instructions?

Digitized work instructions provide clear, step-by-step directions on how each manufacturing task should be performed. They are kept in a centralized database for real-time view of procedures, how-to videos, training opportunities, and more. Companies implement them in order to improve workers’ procedural knowledge, ensure standard work compliance, reduce mistakes, and raise production quality overall.

How can digital work instructions help manufacturers?

Digital work instructions help manufacturers create a more productive workforce that values detail, quality, and learning. Work instructions can be updated to fit best practices, reduce human error, and provide learning opportunities with visual cues like videos, pictures, augmented reality experiences, and more.

Which work instruction software is right for me?

Although there are different software programs out there, Augmentir is the world’s leading connected worker solution, and the only solution that uses AI to personalize instructions based on individual worker proficiency and skill levels.

How Augmentir’s digital solutions can help

Digitizing work instructions is a great start to address manufacturing issues, however, alone, it won’t help completely solve some of the biggest workforce challenges. It’s not enough to simply move from paper-based to digital work instructions.

We must go a step further, for example, Augmentir’s platform provides complete digital workflow authoring tools that allow you to not only quickly convert your paper-based processes to digital work instructions, but also use AI to dynamically personalize them to the needs of your individual workers.

  • Digital work instructions, augmented with visual aids, contextual information, and industrial collaboration tools, help intelligently guide workers through complex jobs
  • Complete workflows allow you to digitize complex business processes
  • Embedded AI dynamically optimizes work procedures and workflows to deliver in-situ training and support

 

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