In many parts of the globe, manufacturers face growing shortages of skilled workers. In the U.S. alone, the “skills gap” could result in a shortage of 2.1 million workers by 2030.*1 However, digital transformation (DX) initiatives have fallen short of expectations. Frontline workers often find digital tools to be poorly designed or mismatched with their needs. Some express hesitation to embrace tools that they believe might ultimately displace them — even if that assumption is not quite correct. In short, worker adoption of digital tools has lagged behind optimistic projections.
How can digital tools be designed to engage more workers? How can they expedite onboarding and training? And, crucially, how can they ensure greater worker well-being — not just productivity? In our latest roundtable, Wei Yuan, who leads digital and industrial solutions research at Hitachi America R&D, speaks with Vignesh Markandan, VP, Manufacturing and Consumer Goods Businesses at Hitachi Digital Services, and Mike Lashbrook, SVP, Digital Strategy and M&A at Hitachi Industrial Holdings America, who share their insights on how companies can improve adoption and alleviate the worker shortage by making digital solutions more “human-centered.” Wei, Vignesh and Mike share stories illuminating how digital solutions can be a seamless and valuable part of workers’ daily routines.
*1 Deloitte and The Manufacturing Institute, “Creating Pathways for Tomorrow’s Workforce Today: Beyond Reskilling in Manufacturing”
Wei: As we all know, the manufacturing industry needs people. Companies have turned to digital transformation (DX) to become more efficient and boost productivity, but they’ve been far from successful. If industry analysts are correct, the success rate of DX in manufacturing is 48 percent.*2 There are many reasons for this, from the lack of clearly and quantitatively defined goals, to the lack of knowledge and skills, high initial costs and the challenge of integrating with legacy systems—the list goes on.
Worker adoption challenges seem particularly entrenched. Adoption of new digital tools remains a challenge. We can develop incredible, innovative solutions, but they don’t have much value if they don’t work for workers.
*2 Gartner, Press Release: “Gartner Survey Reveals Only 48% of Digital Initiatives Are Successful”
Mike: Bringing digital solutions into the factory is more than just a technological change — it’s also an organizational and cultural one. Companies need to do a better job of engaging workers in the solution development and deployment process.
When I first led lean transformations at plants, I’d sit with the operators, rebalancing a line with a pencil and an eraser. Then we got magnet boards. I've worked in the automotive industry and earlier in my career they’d use hōshin kanri — a seven-step strategic planning system. BPD, or Business Plan
Deployment was often done in a nerve center on the floor. It was paper-based, and all the teams would come, meet, and talk. You’d tackle the problem together. That method would emphasize transparency, communication, and visualization.
Then there would be a “go and see” exercise. You’d just walk over to check out a problem — it'd be right there. I've watched people walk into plants and they're like a Bloodhound sniffing out the issue. They can just point to it, no system necessary. We were experiencing what the workers were experiencing. This is the kind of engagement that’s valuable.
Smart gloves and augmented reality
Wei: Let me bring in a success story from when we successfully engaged with workers and everyone reaped the benefits. One of the areas Hitachi America R&D is working on with JR Automation is the smart glove, which is a sensor-based wearable that enhances workers’ sense of touch. Based on each individual worker’s role and needs, the smart glove can be “trained” to support workers in critical decision-making. That includes verifying manual assembly quality or whether a manual operation is being designed properly for frontline workers. It can also be utilized by workers for critical knowledge extraction and self-training.
"Training" Hitachi’s smart glove to bolster worker effectiveness at JR Automation
I found it admirable that a customer raised questions around how we could expand the use case of the smart glove to areas that are critical for their workers, such as safety, well-being and flexibility. That is a great example of human-centered thinking.
Another use case is with our augmented reality-based solution. We often use AR to train workers. Training is a typical application that leverages AR technology, but it can also be used by frontline workers for guided operations and maintenance, especially supporting workers in troubleshooting and remote maintenance work to ensure that they can do their jobs safely.
An AR training solution in action
Current industry practices can be too technology centric. Manufacturers introduce new technologies, and users are expected to simply adapt to them. To your point, Mike, manufacturers tend to focus only on boosting productivity, throughput and quality.
How do we get workers on board, if all we talk about are business goals? What about highlighting the benefits for workers, to help drive their motivation to adopt or to just lower the threshold for adoption so they can take on new roles?
From our experience, the difficulty isn’t in convincing top management. It’s in engaging factory floor workers. They’ll ask: “How would this affect flexibility, safety, and job satisfaction? How does it impact our day-to-day operations?” In other words: “What’s in it for me?”
Mike: All good points, although one thing we need to be mindful of regarding wearables is that, aside from ergonomic issues, we have to be very careful that they are not seen as a way to police an operator. It's got to be introduced from the very beginning as, “Hey, this is going to help you be more effective, more efficient in your job, and make your job safer and more convenient.” There's some hesitation when it comes to wearables and cameras because they get introduced as a continuous improvement tool. If they ever get abused and used as a monitoring tool, you've just lost all credibility with workers.
A ticketing system on a farm?
Wei: Vignesh, what kind of other barriers to adoption have you seen?
Vignesh: Although not in the manufacturing industry, here’s a classic example of the disconnect between management goals and worker needs. I was on a farm recently where they harvest blackberries and strawberries. The corporate team told me they’re phasing out the basic ticketing system service, which they’d paid licensing fees for hundreds of farmer workers to use. It turned out they weren’t using it. And that system didn’t even involve any cutting-edge software or any Industry 4.0 initiative.
The system was set up so that if something wasn’t working, they wanted the workers to log into a portal — on a farm, remember — and put in the information. It just doesn't make sense!
This is why adoption often fails: we don't think from the user's perspective. That's where design thinking comes into the picture — the journey mapping of an individual user. What does their “day in a life” look like? And if I'm going to expect them to use a tool in their particular walk of life, how can I make it easy for them to use? That perspective is extremely important and is often overlooked.
The role of human-centered technology
Wei: I completely agree. And the thing is, human-centered design has been around for decades. It’s just an approach in which we put the user’s needs and preferences front and center when we develop solutions. Human-centered solutions should empower people, keep them safe, and encourage their creativity.
These solutions should work for as many users as possible, not just more specialized workers. A human-centered approach should democratize technology through broad accessibility and make manufacturing jobs possible for more kinds of workers. I also believe that human-centered design should bring about positive impacts, not only oriented around business values, but around human life and the improvement of society.
Vignesh: In our everyday life, we take a lot of things for granted, like using a rideshare app or booking travel on our mobile phones. Everything is designed in such a way that we can conduct much of our lives via mobile phone, right? Even airlines understand that, if you go to their app, a lot can be achieved without having to call anybody or wait for anybody. That intuitiveness needs to be built into everything we do, including the factory floor. That for me is human-centered design.
Alan Kay, who is the father of object-oriented programming, famously said: “Technology is anything that didn't exist when you were born.” So, a kid born today has generative AI, Alexa, and Google, and they just interact with them like nobody’s business. They’re born into it. It’s a way of life. My kids use generative AI in ways that I can't fathom. If you can enable users to adopt a technology that they were not born into, that’s success.
Mike: If you look at the interfaces we put on equipment, they’re obviously designed by engineers. We have young kids coming out of school now (into the workforce) and there’s no reason that the interface shouldn't look more like a mobile phone app and be more user-friendly.
You need to design the systems so that they’re understandable for the operators, for the maintenance workers, since they’re really the number one consumer. From day one, you should be asking them, “What do you need to solve your problems? How do I make your life better?” When they're included as part of the process, they buy right in. Engage the team, the operators, the maintenance workers, the team leaders, and then deploy it. Bring them on the journey.
What happens often in digital transformation projects is that the focus is on benefits to executive management. We want this nice dashboard up at the plant manager-level and the executive-level. We have these rolled-up metrics and KPIs. That's going to help somebody have a pretty chart on their PC, but you lose something in the process — for example, lean thinking and lean concepts.
Generative AI: better behind the scenes
Wei: Although AI is not talked about as being human-centered, it can play a critical role in making manufacturing systems easier to use. AI enables “less skilled” workers to participate in solving manufacturing optimization challenges, from production scheduling and quality control, to realizing optimization targets such as worker productivity, sustainability, and resilience. Beyond closing the skills gap, I’m confident that the democratization of technology will help create a more positive work culture and increase manufacturers’ competitiveness.
Vignesh: Another example of human-centered AI is in the logistics industry. The customer is Penske, which is a Hitachi America R&D use case involving 390,000 trucks that the customer leases. They have 90,000 repair shops around the country.
They can now predict problems in Class 8 trucks. The trucks tend to be rerouted three hours before they fail. Penske made the wise decision to allow mechanics in repair shops to either accept recommendations for repairs from an AI model or attempt repairs themselves.
If their repairs didn’t work and the truck came back, or if the truck was sent to another location for the same repair, then there was a feedback loop to the mechanic saying, “The truck is in another shop going through the same repair.”
The application is a huge success. Today they have almost 200,000 trucks that employ this predictive algorithm. They are now at a point where the operation runs continuously, with minimal interruption.
That feedback loop boosted adoption rates significantly. Mechanics now feel empowered enough to use it daily and, thanks to the expanded use, there’s a 90 percent accuracy rate. And all we did was give them a choice! That's a great success story.
Towards human-machine collaboration
Wei: People often talk about unmanned, “lights-out” factories. While that may be possible for certain scenarios, right now, in America, we have close to 13 million workers on factory floors, and most projections for the next decade show the same number of workers. Workers will still be critical to the shop floor. But we can significantly enhance the way human workers collaborate with manufacturing systems by making machines smarter and by making them easier to interact with by using generative AI. Machines will be able to understand workers, adapt to workers’ needs, and support human workers in critical decision making.
Mike: Here we are in 2024, and we still don’t have lights-out factories. I think we’ll see more automation in 10 years, and we’ll also see a lot more technology augmenting the work of operators on the shop floor.
We won’t replace operators with AI. We’ll take some of the administrative and manual stuff away so they can focus on value-added work.
We're not going to have humanoid robots running around doing everything. Factories will look much like the way they do today. But, for example, drones will be able to do maintenance activities. Other tasks that we used to have workers do were super dangerous, like getting up into the rafters in plants, we’ll be able to fly a drone up there and do them.
In jobs where safety is number one, if we can find a solution that gets the person out of doing a dangerous task, we'll jump at those.
Wei: Exactly. Cobots are a perfect example of human-centered solutions. Hitachi uses cobots alongside human staff in some of our factories in Japan for assembly work. Because robots can offer incredible precision, we're leveraging them to do certain tasks, such as screening and inserting parts. But we also exclusively use human workers for other tasks, like wiring, which is very difficult for robots to do. This brings the human and the cobot together. We’re prioritizing flexibility here.
In these cases, we can realize improved performance, in terms of throughput and quality while also empowering operators to avoid repetitive work, to stay safe, and to perhaps focus on higher-level tasks more fitting for people.
Vignesh: Sometimes we like to externalize the challenges we face. When referring to seniors, we are prone to say, for example, that “their generation just doesn’t want to use these tools.” But many of them, for example, shop online.
How is it that a different generation can adopt technology, but when it comes to manufacturing technology, they are not able to adopt it? Who is failing here? That’s how I like to think. It allows me to solve the problem for people rather than making them the problem. Maybe it’s me who’s not understanding their perspective when it comes to implementing these things on the shop floor.
Human-machine collaboration is possible. We just need to be more human-centered in our solutions.
Wei: Vignesh, I can’t think of a better way to close our discussion. Thank you both for taking the time to share your insights.
Conclusion
Addressing the technology adoption problem is essential to easing the worker shortage in manufacturing. Involving workers in the design and development of digital solutions is key. Human-centered solutions like Hitachi’s smart glove offer manufacturers a turnkey approach to engaging, training and empowering workers. Emerging technologies such generative AI and AR also have the potential to transform how workers do their jobs, on and off the factory floor. If manufacturers are going to attract and retain workers, they need to democratize access to technology. They need to put a premium on people, as well as the products they make.
(This discussion has been edited for clarity.)
Profiles
Vignesh MARKANDAN
Vice President, Head of Manufacturing and Consumer Goods Business,
Hitachi Digital Services, LLC
Vignesh Markandan is vice president and the head of manufacturing and consumer goods business at Hitachi Digital Services. His tenure of over 25 years has been marked by a steadfast commitment to steering clients towards successful business outcomes. An expert of both discrete and process manufacturing sectors, Vignesh’s passion lies in unraveling complex business challenges. He achieves this by strategically harnessing the power of cutting-edge digital technologies, coupled with his business and technical acumen. His journey through the digital landscape is punctuated with significant contributions to digital transformation, innovative product development, and service delivery management.
Mike LASHBROOK
Sr. Vice President, Digital Strategy and M&A,
Hitachi Industrial Holdings America, Inc.
and
Vice President, Digital Solutions,
JR Automation Technologies, LLC
Mike Lashbrook is an experienced executive currently serving as senior vice president for digital strategy and M&A at Hitachi Industrial Holdings America since March 2023, and as a member of the board of directors at Flexware Innovation since September 2022. Mike has held the position of vice president of digital solutions at JR Automation since March 2020 and has been an advisor at Tour Engine, Inc. since January 2018. Prior roles include vice president at Esys Automation and involvement as an advisor for multiple startups and companies, including Lohum and an AI startup. With extensive experience in manufacturing leadership at General Motors from 2013 to 2017, he oversaw operations across multiple sites in China.
Mike holds a master's degree in business administration from Harvard Business School and additional degrees in manufacturing systems and engineering from Kettering University.
Wei YUAN, PhD
Director and Manager of the Industrial Innovation Laboratory,
Research & Development Division,
Hitachi America, Ltd.
Wei Yuan is a director at Hitachi America R&D, also serves as the leader of the Hitachi Global One Team for industrial solutions. He oversees the incubation and development of human-centric digital and automation solutions for smart factory and warehouse applications. Wei drives the creation of digital service business through collaboration with industry customers, Hitachi Group companies and front business units, such as Hitachi Industrial Holdings America, JR Automation and Hitachi Digital. He has over 20 years of experience in research and development and 15 years of experience working in various factory environments, collaborating with the factory shopfloor and management teams on solution implementation.
Wei holds a doctoral degree in metallurgy and has authored over 40 publications, including review papers and a book.
