Posts

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.

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.

 

Dust Away One-Size-Fits-All Work Instructions

AI-powered technology may be the missing puzzle piece for today’s workforce crisis.

Are you still printing work instructions and operating manuals? If so, we need to have a serious chat! Maybe you invested in “going digital” a while back and think your work is done. You’re not alone. It was considered “groundbreaking” when PDF files made their way to the factory floor. 

The first generation of digital work instructions were birthed after learning 46 percent of field technicians claimed paperwork and administrative tasks were the worst part of their day-to-day job. No argument here. Completing and filing paperwork is time-consuming and there is potential for lost information. There was an obvious upside to going digital, except for no longer being able to tell your supervisor that your dog ate your worker performance report. 

But even now that technology is ready for the archives. An estimated $1.3 trillion (and counting!) has been spent on digital transformation initiatives as the online connected workplace and market continue to move at a rapid pace. 

We are no fortune tellers, but studies show that 25 to 31 percent of 3.3. million business service jobs will be automated in the next decade. This doesn’t mean everyone is being replaced by robots. On the contrary. It means technology is improving to help workers do their jobs even better. Manufacturing companies need to be prepared to hop on this next-generation train if they aren’t already.

Move over one-size-fits-all training and work instructions 

The individualized, real-time, connected worker platform is here. Let us emphasize individualized. Connected worker platforms are being implemented in myriad industries, from automotive to food processing. Any industry which is adapting daily to the constant shifts and pressures of the global economy. Regardless of the industry, standard digital work instructions are no longer effective. They do not reflect the real-time changes happening in the operation, such as order fulfilment and materials inventory, or equipment maintenance needs and the capabilities of the workers operating the machines. Imagine working on the manufacturing floor for five years and handed with the same standardized work instructions as the new hire.

Does this make sense? Not anymore. Not when AI-based technology is changing what’s possible. And what’s different about this latest wave of technology that makes it so special? It’s built around optimizing the performance of people (Gasp.)

Change is inevitable. Growth is optional. – John C. Maxwell

A marriage made in heaven–the next generation of workers is ready for a digitally connected workplace

Recruiting and retaining talented workers is one of the greatest challenges facing operations today. We get it. But there’s good news. As one generation of workers readies for retirement, another is stepping up to fill the gap. Gen Z is overflowing with talented innovators in the tech world having grown up surrounded by non-stop advancements and devices. Need one of them to look somebody up in the phone book? Forget it. But need assistance when your home computer suddenly “dies”? These are your people. 

It’s more than video games. Their education has been largely based on a digital foundation. Nearly every function of their daily lives has an element of connectivity to the broader online world. You could say this generation is hardwired to respond best to customized digital learning platforms. It’s their love language. And so the potential to drastically improve productivity is real.

The beauty of the digitally connected worker–could they be “the One”?

The digitally connected worker has all the right stuff for a long-lasting relationship with your operation. The digital training and work instruction platform holds their unique inventory of skills, goals, and performance history, and works with them to become a better version of themselves on the floor. Workers whose individual needs are supported are better, more engaged employees. They have the self-confidence – as well as the tools and specific instructions – to address problems head on when they arise. An investment in AI-powered technology is an investment in a stable, adaptable, and reliable workforce.

Are you and your workforce ready to take this next step in digitization? Contact Augmentir to start the conversation. Together let’s step into the full potential that this generation has to offer to improve your operational efficiency.

Webinar: Delivering Effective Performance Support through Workflow Learning

Today’s industrial workforce is changing in real-time – who shows up, what their skills are, what jobs they need to do, is a constantly moving target. The traditional “one size fits all” approach to training, guidance, and performance support is fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality […]

Today’s industrial workforce is changing in real-time – who shows up, what their skills are, what jobs they need to do, is a constantly moving target. The traditional “one size fits all” approach to training, guidance, and performance support is fundamentally incapable of enabling today’s workers to function at their individual peak of safety, quality and productivity.

Watch the recording of our recent virtual roundtable of industry leaders as they discussed proven approaches to delivering performance support and modern training approaches for today’s industrial workforce.

 

The Top 100 Entrepreneurs of 2022

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.

Alumni Spotlight recently announced The Top 100 Entrepreneurs of 2022, which recognizes innovative and devoted entrepreneurs dedicated to driving economic growth across the country, stimulating new employment opportunities in nearly every industry. In addition, those selected have shown dedication to further developing technologies that bring progress, economic growth, community development, and income generation for a brighter future. We are excited to announce that Augmentir’s CEO and Co-Founder, Russ Fadel, was named as one of the Top 100 Entrepreneurs of 2022! 

Russ graduated from Duke University with an undergraduate degree in mechanical engineering. After graduating, he went on to found four successful manufacturing software companies prior to Augmentir including Wonderware Software in 1987, Lighthammer (acquired by SAP) in 1997, and in 2008 ThingWorx (acquired by PTC). In 2017, Russ recognized that the most important asset, the human workers, were under-served. He co-founded Augmentir, the world’s only AI-powered Connected Worker platform, designed to increase the productivity and quality of processes involving frontline workers.

Since 2017, Augmentir has helped close the rapidly expanding skills gap in the industrial frontline workforce through the use of Artificial Intelligence, providing personalized guidance and support to manufacturing and service workers, enabling them to perform complex operational and maintenance tasks at their personal best. The suite of AI-powered connected worker tools helps industrial companies to deliver effective skills management, training, collaboration, and point of work support for today’s more dynamic industrial workforce. Augmentir’s software platform is already being used worldwide by leading industrial companies and organizations, including Colgate-Palmolive, Cisco, Baker Hughes, the U.S. Air Force, and Hunter Industries to digitize and optimize frontline work and deliver significant growth and continuous improvement in the areas of manufacturing, maintenance, service, and quality. Thanks to Russ’s leadership and guidance, Augmentir entered 2022 with triple revenue growth and is expanding its next generation Connected Worker offering globally.

 

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