Augmented Ops - Episodes Tagged with “Operations”

Modernizing the Industrial Base: Readiness, Resilience, and the Road Ahead

Tulip — Thu, 02 Apr 2026 00:15:00 -0400

Modernizing the U.S. industrial base is no longer a long-term goal. Between geopolitical competition, workforce constraints, and rising cybersecurity demands, manufacturers are under pressure to rethink how production systems are built and operated.

Clark Dressen, CTO of MxD, joins the show to explain how this transformation is taking shape across the defense industrial base and broader manufacturing ecosystem. As a public-private partnership funded in part by the Department of Defense, MxD works to connect emerging technologies with real-world production environments.

The conversation focuses on what modernization actually requires. Not digital transformation for its own sake, but applying technology to solve specific operational problems around quality, productivity, and consistency. Clark shares how tools like sensors, digital twins, and AI are being introduced into legacy environments to reduce reliance on tribal knowledge and create more repeatable processes.

The episode also explores the structure of the industrial base, where small and mid-sized suppliers make up the majority of the defense supply chain but often lack the resources to meet growing cybersecurity and compliance requirements. As workforce transitions accelerate, the focus shifts toward capturing expertise, improving how work is executed, and building more resilient production systems.

Watch the full episode on YouTube: https://youtu.be/T2bkZvyK5kU

Augmented Ops is a podcast for industrial leaders, citizen developers, shop floor operators, and anyone who cares about what the future of frontline operations will look like across industries. This show is presented by Tulip, the Frontline Operations Platform. You can find more from us at Tulip.co/podcast or by following the show on LinkedIn.

Special Guest: Clark Dressen.

Regional Ecosystems of Manufacturing: The Foundation of Industrial Strength

Tulip — Thu, 19 Mar 2026 00:15:00 -0400

What actually makes a region strong in manufacturing?

In this episode, Gillian Catrambone sits down with Beatriz Gutierrez, CEO of CONNSTEP Inc., Connecticut’s Manufacturing Extension Partnership (MEP), to explore how regional ecosystems, through MEPs, workforce programs, and coordinated resources, create the foundation for industrial strength.

Beatriz breaks down how manufacturers are navigating labor constraints, adopting automation incrementally, and rethinking supply chains in a more volatile environment. The conversation also highlights what separates effective regions, including strong talent pipelines, connected institutions, and easier access to capital, training, and support.

She closes with practical guidance for operations leaders. Focus on critical processes, plan for the long term, and approach transformation step by step rather than waiting for perfect conditions.

Watch the full episode on YouTube: https://youtu.be/ZJO0bbYSGII

Special Guest: Beatriz Gutierrez.

The State of Reshoring: Supply Chains, Strategy, and the Future of US Manufacturing

Tulip — Thu, 05 Mar 2026 00:15:00 -0500

Global supply chains are being rewired in real time. From tariffs and geopolitics to labor constraints and energy infrastructure, manufacturers are navigating a level of volatility few have experienced before.

Rosemary Coates, Founder and Executive Director of the Reshoring Institute, joins the show to unpack what’s actually happening beneath the headlines. Drawing on recent executive interviews and location studies, she explains why many companies are pausing major decisions, how “China plus one” strategies are evolving, and what reshoring really requires beyond political rhetoric.

For operations leaders, the conversation moves from macro forces to practical considerations: evaluating total landed cost beyond labor, balancing capital intensity with workforce availability, selecting locations with infrastructure in mind, and building resilience through diversified manufacturing footprints. While the path forward is complex, Rosemary outlines why advanced, higher-skilled manufacturing still presents meaningful opportunity for U.S. growth.

Watch the full epsiode on YouTube

For more on this topic, Rosemary hosts The Frictionless Supply Chain podcast, covering supply chain strategy and global production shifts.

Special Guest: Rosemary Coates.

From the Classroom to the Shop Floor: Building the Future Industrial Workforce

Tulip — Wed, 18 Feb 2026 00:15:00 -0500

Manufacturing is undergoing a generational shift. As experienced workers retire and automation accelerates, the industry must solve both a workforce shortage and a skills gap — and it must do so simultaneously.

Jacob “MFG Kid” Sanchez is a well-known manufacturing influencer and content creator, and a vocal advocate for bringing new talent into the industry. With hands-on shop floor experience and a growing platform dedicated to promoting automation and modern manufacturing careers, he works to make the industry more visible, accessible, and appealing to the next generation.

Check out Jacob’s newly launched Axis community — a brand-neutral space for automation, robotics, and manufacturing professionals to connect, learn, and collaborate.

In this conversation, Jacob and Natan explore how manufacturers can generate genuine interest in industrial careers, rethink how technical skills are taught and developed, and draw lessons from apprenticeship models in countries that consistently produce highly skilled manufacturing talent.

Watch the full episode on YouTube

Special Guest: Jacob "MFGKid" Sanchez.

The Need for Speed in Life Sciences

Tulip — Thu, 05 Feb 2026 00:15:00 -0500

The life sciences industry has long justified slow digital adoption through regulation. But as technology adoption accelerates faster than guidance, that logic is breaking down.

In this episode, Michelle Vuolo and Gilad Langer discuss why speed has become a defining challenge for pharma and medical device manufacturers. Drawing on experience from ISPE, quality leadership, and decades in regulated operations, they explore validation 4.0, cultural resistance to risk-based thinking, and how AI is reshaping quality and compliance work.

The conversation examines what it really takes for life sciences organizations to move faster without losing control — and why waiting for perfect regulatory clarity is no longer a viable strategy

Watch the full episode on YouTube: https://youtu.be/SPJz8_cFYM4

Special Guest: Dr. Gilad Langer.

The Human Infrastructure of Manufacturing with Stacey Weismiller of AMFI

Tulip — Thu, 22 Jan 2026 00:15:00 -0500

Manufacturing is often discussed in terms of technology, productivity, and investment — but rarely in terms of people as infrastructure. In this episode of Augmented Ops, Stacey Weismiller, Founder of the American Manufacturing Futures Institute, joins Natan Linder to reframe the conversation.

Stacey draws on her background spanning manufacturing, economic development, and global policy to explore why people, access, and community must sit at the center of industrial renewal. Together, they discuss workforce participation, civic manufacturing, equitable growth, and how AI can augment human work without eroding trust or dignity.

The conversation spans everything from factory jobs and childcare to resilience, reindustrialization, and why manufacturing needs a new narrative — one that values stewardship as much as efficiency.

Watch the full episode on YouTube.

Special Guest: Stacey Weismiller.

The Real Problem AI Needs to Solve in Manufacturing

Tulip — Thu, 15 Jan 2026 09:00:00 -0500

Read about Tulip’s $120M Series D 👉 http://tulip.co/press/tulip-secures-120m-series-d/

In this conversation, Chris Luecke, host of the Manufacturing Happy Hour podcast, joins Natan Linder to discuss AI in manufacturing, and how Mitsubishi Electric’s lead investment in Tulip’s $120M Series D helps to accelerate our mission to scale our composable platform, support an open ecosystem for frontline operations, and supports AI-enabled and human-driven innovation.
Key themes from this conversation include:
• Why "software-defined manufacturing" is essential for modern supply chains.
• The rise of the AI process engineer, and real-world implications of AI adoption among frontline process engineers.
• The importance of building a transparent, human-first culture in frontline operations.

Augmented Ops is a podcast for industrial leaders, citizen developers, shop floor operators, and anyone else that cares about what the future of frontline operations will look like across industries. This show is presented by Tulip, the Frontline Operations Platform. You can find more from us at Tulip.co/podcast or by following the show on LinkedIn.

Special Guest: Chris Luecke.

AI at the Crossroads of Regulation and Innovation

Tulip — Thu, 08 Jan 2026 12:00:00 -0500

AI is rapidly reshaping life sciences manufacturing—but as intelligent systems move into regulated environments, questions around validation, governance, and trust become unavoidable.

In this episode of Augmented Ops, host Michelle Vuolo, Head of Quality at Tulip, is joined by Bryan Ennis, Chief Quality Officer and Founder of Sware, and Martin Heitmann, of the Triality Group. Together, they explore what it really takes to deploy AI responsibly in pharma, biotech, and medtech operations.

The conversation examines why many AI initiatives stall at the pilot stage, how validation practices must evolve for probabilistic systems, and where organizations are already seeing real value—from predictive maintenance to quality signal detection and validation automation. They also discuss emerging regulatory guidance, including Annex 22, and why regulators are not anti-AI—but deeply skeptical of black-box systems.

Throughout the discussion, a consistent theme emerges: successful AI adoption is less about the technology itself and more about process design, data quality, human oversight, and building evidence that systems are safe, transparent, and fit for purpose.

This episode offers a grounded, experience-driven perspective on how life sciences organizations can move from experimentation to scale—without compromising patient safety or compliance.

Watch the full episode on YouTube: https://youtu.be/7keK_4zDaTg

Special Guests: Bryan Ennis and Martin Heitmann.

Giving Robots "Common Sense": Inside RightHand Robotics with Yaro Tenzer

Tulip — Thu, 18 Dec 2025 00:15:00 -0500

Robotics has promised to transform manufacturing and logistics for decades — but turning intelligent machines into reliable, everyday operators remains hard. In this episode of Augmented Ops, Natan Linder sits down with Yaro Tenzer, co-founder and CEO of RightHand Robotics, to talk about what it actually takes to deploy AI-powered robotics in real operational environments.

Yaro shares lessons from building robotic systems that operate in the messiness of the real world — where data is imperfect, edge cases are constant, and reliability matters more than demos. Together, they discuss why so many robotics pilots struggle to reach production, how machine learning improves through real-world feedback, and what operations leaders should understand before investing in automation.

The conversation explores the intersection of robotics, AI, and operations — focusing on practical constraints, system design, and the human decisions that determine whether advanced technology delivers value or stalls on the shop floor.

Watch the full episode on YouTube: https://youtu.be/a06GA7TvI8Y

Special Guest: Yaro Tenzer.

The Future Process Engineer with Chris Luecke of Manufacturing Happy Hour

Tulip — Thu, 04 Dec 2025 00:15:00 -0500

What does the future of process engineering look like in an era shaped by AI, automation, and rapid operational change? In this episode, Chris Luecke joins Natan Linder to explore how the role is evolving, what still defines great engineering, and why human judgment remains essential on the modern shop floor.

Chris is the host of Manufacturing Happy Hour and one of the most connected voices in the industry. Before stepping behind the microphone, he spent years as a process engineer at Anheuser-Busch and later worked across sectors with Rockwell Automation—giving him a rare vantage point on how factories actually run and how engineering teams solve problems.

Natan and Chris discuss the shift from reactive troubleshooting to systems thinking, how culture shapes the pace and quality of improvement, and why the most effective way to introduce AI is to aim it at the tasks teams collectively find painful. They also examine the idea of “Shenzhen Speed,” how faster design and production cycles influence global competitiveness, and what manufacturers elsewhere can learn from regions that move quickly.

This conversation offers an on-the-ground view of how engineering work is changing and what the next generation of process engineers will need to thrive.

Watch the full episode on YouTube

Special Guest: Chris Luecke.

AI, Industry, and the Human Story with MIT’s David Mindell

Tulip — Thu, 13 Nov 2025 00:15:00 -0500

AI is often described as a revolution, but every technological leap has deep roots in the human story. In this episode of Augmented Ops, MIT Professor and author David Mindell joins Tulip CEO Natan Linder to discuss how history can help us navigate the rise of intelligent systems.

Mindell, a historian, engineer, and entrepreneur, shares insights from his latest book, The New Lunar Society, which traces the origins of the Industrial Revolution and the people who built it. He draws connections between the 18th-century innovators who powered the first era of mechanization and today’s engineers shaping AI. Every tool, he argues, embeds human skill, judgment, and culture; from the earliest steam engines to modern autonomous systems.

Their conversation examines the enduring questions that define manufacturing and technology: How can new tools expand opportunity instead of narrowing it? What does responsible innovation look like in an age of automation? And how can societies balance ambition, governance, and trust while embracing change?

Through stories of invention, work, and rediscovery, Mindell reminds us that progress has always been a human endeavor. Technology evolves, but the drive to create, understand, and improve remains constant.

Watch the full episode on YouTube

Special Guest: David Mindell.

AI for Operations: From Everyday Tools to Agentic Systems

Tulip — Thu, 30 Oct 2025 00:15:00 -0400

Manufacturing is entering a new phase of AI adoption, one where intelligent systems don’t just generate insights but take action in context. In this episode of Augmented Ops, host Mason Glidden, Tulip’s Chief Product Officer, is joined by Olga Stroilova, Group Product Lead, and Pete Hartnett, Group Product Manager, to discuss how agentic AI is redefining what’s possible on the factory floor.

Together, they unpack the evolution from predictive and generative AI to agentic systems capable of autonomous, goal-driven behavior while keeping people firmly in the loop. They examine why many pilots stall before production, how governance and culture shape adoption, and why “human oversight by design” is becoming the new standard for responsible AI in manufacturing.

Drawing from Tulip’s own roadmap and customer experiences, the team highlights how features like AI Composer, Tulip Agents, and context-aware workflows are helping users close the insight-to-action gap, scale AI safely, and unlock new forms of operational leverage.

Rather than imagining a future without people, the episode points to a more realistic vision of AI in manufacturing: one where systems evolve, but human judgment remains the foundation of progress.

Special Guests: Olga Stroilova and Pete Hartnett.

Operations Calling 2025 Recap: From AI Hype Into Real World Results

Tulip — Thu, 16 Oct 2025 00:15:00 -0400

Kicking off Season 6, Natan and Tulip CMO Madilynn Castillo reflect on Operations Calling 2025—recorded just after nearly 800 manufacturing leaders, engineers, and frontline pros converged at Tulip HQ for Tulip’s biggest event to date. More than a showcase of technology, this two-day experience blended strategy, execution, and genuine community. Attendees dove into headline keynotes, fireside chats, interactive workshops, and panels, led by senior voices and industry experts driving the new era of manufacturing.

The episode captures how this convergence marked a real inflection point: AI moving from hype to hands-on tools like Tulip Agents, composable systems scaling across teams, and the shift from digital transformation to continuous transformation on the shop floor. Through live demos, open learning, and collaborative problem-solving, participants saw—and built—the next wave of operations-led innovation.

Packed with post-event momentum, Natan and Madi share stories and lessons that reveal how practical AI, human-centered design, and community are reshaping manufacturing’s future.

Check out all the Operations Calling Sessions!
Natan's Keynote
The Next Shift: AI-Driven Transformation of the Connected Factory
Tulip Roadmap Session

Special Guest: Madilynn Castillo.

Reindustrializing in 2025 — AI, Scale, and the Future of U.S. Manufacturing with MIT’s Liz Reynolds

Tulip — Thu, 14 Aug 2025 00:15:00 -0400

In this bonus episode, our guest is Liz Reynolds, manufacturing and workforce expert at MIT and strategic advisor to Tulip..

Fresh from Detroit's Reindustrialize conference, Liz and Natan share key insights on America's urgent push to bring manufacturing back home. They explore the "Spring of momentum" in reindustrialization efforts, from AI moving beyond hype to real implementation on the shop floor, and break down the massive scale challenges facing US manufacturers across critical sectors.

Drawing from major industry conferences including Reindustrialize, the Hill and Valley Forum, Industry Studies Association, and MIT's Initiative for New Manufacturing, she explains strategic workforce development approaches to address the 400,000 manufacturing worker shortage and the Department of Defense's $1 trillion budget impact on industrial capacity. Reynolds sheds light on how this Spring's discussions and strategic planning around technology adoption and workforce training are beginning to take concrete shape as the real work accelerates into Fall.

Special Guest: Elisabeth Reynolds.

Episode 134: Building Industrial Architectures with MQTT with HiveMQ’s Dominik Obermaier

Tulip — Wed, 27 Mar 2024 00:30:00 -0400

This week’s guest is Dominik Obermaier, Co-Founder and CTO of HiveMQ.

With over 10 years of experience serving on the MQTT technical committee and helping organizations build their data foundations using HiveMQ’s MQTT platform, Dominik shares his deep expertise on the technology. He explains what makes MQTT such an important communications protocol, why the emergence of the Unified Namespace matters for manufacturers, and debates the merits of on-prem vs. cloud solutions.

Augmented Ops is a podcast for industrial leaders, shop floor operators, citizen developers, and anyone else that cares about what the future of frontline operations will look like across industries. This show is presented by Tulip, the Frontline Operations Platform. You can find more from us at Tulip.co/podcast or by following the show on LinkedIn. HiveMQ is a Tulip Technology Ecosystem Partner.

Special Guest: Dominik Obermaier.

Episode 133: Rethinking Our Approach to AI with Dr. Jay Lee

Tulip — Wed, 13 Mar 2024 00:15:00 -0400

This week’s guest is Jay Lee, Director of the Industrial AI Center at the University of Maryland.

Dr. Lee shares his experiences from the early days programming machines with punch cards, to eventually developing advanced machine learning applications for industry. He explains how AI and ML are reshaping manufacturing, the workforce, and global supply chains. Plus, he lays out his vision for how our education system needs to change in order to train the next generation of AI practitioners.

Special Guest: Jay Lee.

Episode 132: Open Source Software for Manufacturing with UMH's Alex Krüger

Tulip — Wed, 28 Feb 2024 00:30:00 -0500

This week’s guest is Alex Krüger, Co-founder and CEO of United Manufacturing Hub, or UMH.

Alex shares his journey from working on integration projects in consulting fresh out of college, to founding UMH and building an open source alternative to the offerings from incumbent vendors. He breaks down the role of the open source software movement in manufacturing, how the Unified Namespace architecture compares to the traditional ISA-95 model, and how IT can best enable OT to solve problems. Plus, he shares his vision for how microservice-based MES solutions can disrupt the existing monolithic applications.

Special Guest: Alex Krüger.

Episode 131: MQTT, Unified Namespace, and The New Industrial Data Stack with Litmus’s Vatsal Shah

Tulip — Wed, 14 Feb 2024 00:30:00 -0500

This week’s guest is Vatsal Shah, Founder and CEO of Litmus.

Vatsal discusses his journey from an automation engineer at Rockwell, to building a new industrial data platform from the ground up after becoming frustrated with the limitations of the offerings from established vendors. He discusses manufacturers’ exodus from on-prem to cloud systems, the pros and cons of data protocols like MQTT and Sparkplug B, and why the Unified Namespace architecture is getting so much attention. Plus, he shares his vision for the future of edge computing and how an open ecosystem of interoperable tools is transforming the industry.

Special Guest: Vatsal Shah.

Episode 130: Democratization, Gen AI, and the Future of Industrial Analytics with Seeq’s Lisa Graham

Tulip — Wed, 31 Jan 2024 00:30:00 -0500

This week’s guest is Dr. Lisa Graham, CEO of Seeq.

Dr. Graham discusses her journey from process engineer, to using Seeq’s platform as a customer, and now leading the company as CEO. Drawing on her extensive experience in operations, she discusses how advanced analytics, generative AI, and the emergence of an interoperable technology ecosystem are reshaping industries. Plus, she shares best practices for IT/OT collaboration, her vision for the future of historians, and how the democratization of data science is paving the way for a more efficient and sustainable future in operations and manufacturing.

Special Guest: Lisa Graham.

Episode 129: AI and the Human Element in Industry 4.0 with Jeff Winter

Tulip — Wed, 17 Jan 2024 00:30:00 -0500

This week’s guest is Jeff Winter, Sr. Director of Industry Strategy for Manufacturing at Hitachi Solutions.

Jeff offers his insights into the history of the Industry 4.0 movement and how he expects it to evolve in the coming years. His discussion highlights the balance between AI and human ingenuity, the role of frontline workers in an increasingly automated manufacturing environment, and the untapped potential of manufacturing data.

Special Guest: Jeff Winter.

Episode 121: Looking Back and Looking Ahead

Tulip — Wed, 23 Aug 2023 00:15:00 -0400

In this special episode, Trond introduces Natan Linder, CEO of Tulip and co-author of Augmented Lean, as the new host of Augmented Season 4. Trond and Natan review four great interviews from 2022, and Natan previews what’s to come in 2023–with new episodes that go beyond interviews to include brainstorms, debates, and the occasional stream of consciousness.

Episode 104: A Scandinavian Perspective on Industrial Operator Independence with Johan Stahre

Tulip — Wed, 30 Nov 2022 00:00:00 -0500

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is "A Scandinavian Perspective on Industrial Operator Independence." Our guest is Johan Stahre, Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Human-centered automation is the only kind of automation that we should be thinking about, and this is becoming more and more clear. Operators are fiercely independent, and so should they be. This is the only way they can spot problems on the shop floor, by combining human skills with automation in new ways augmenting workers. It seems the workforce does not so much need engagement as they need enablement. Fix that, and a lot can happen.

Transcript:

TROND: Welcome to another episode of the Augmented Podcast. Augmented brings industrial conversations that matter, serving up the most relevant conversations on industrial tech. Our vision is a world where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is A Scandinavian Perspective on Industrial Operator Independence. Our guest is Johan Stahre, Professor and Chair of Production Systems at Chalmers University in Sweden. In this conversation, we talk about how the field of human-centered automation has evolved, the contemporary notion of operator 4.0, Scandinavian worker independence, shop floor innovation at Volvo, factories of the future, modern production systems, robots, and cobots in manufacturing.

Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Johan, Welcome. How are you?

JOHAN: I'm fine, thank you, Trond. It's really nice to see you.

TROND: Yeah, likewise.

JOHAN: Fellow Nordic person.

TROND: Fellow Nordic person. And I apologize for this very American greeting, you know, how are you? As you know, I'm from the Nordic region. I actually mean it, [laughs] you know, it was a question. So I do wonder. [laughs]

JOHAN: I'm actually fine. It's just ending the vacation, so I'm a little bit sad about that because everyone...but it's a very nice time now because the rest of the world seems to be on vacation, so you can get a lot of work done.

TROND: I concur; that is a wonderful time. Johan, I wanted to just briefly talk about your exciting background. You are an engineer, a mechanical engineer from Sweden. And you had your initial degree from Linköping University. Then you went on to do your Ph.D. a while back in manufacturing automation, and this was at Chalmers, the University in Sweden. And that's where you have done your career in manufacturing research.

You are, I think, the first Scandinavian researcher certainly stationed currently in Sweden that we've had on the podcast. So I'm kind of curious, what is manufacturing like in Scandinavia? And what is it that fascinated you about this topic so that you have moved so deeply into it?

JOHAN: Manufacturing in Sweden is the core; it's the backbone of our country in a sense. We have statistically too many large manufacturing companies in Sweden as compared to, I mean, we're only 10 million people, but we have like 10, 12 pretty large companies in the manufacturing area in automotive but also in electronics like Ericsson, you have Volvo, we have SKF. We have a lot of big companies.

Sweden has an industrial structure that we have several small companies and a couple of large companies, not so many in the middle section there. This happened, actually, in the 1800s somewhere. There was a big growth of big companies, and there was a lot of effort from the government to support this, and that has been continued. So the Swedish government has supported the growth of industry in Sweden, and therefore we have a very strong industry and also quite good digital growth and maturity.

TROND: So the Scandinavian background to me when I was there, I remember that one of the things that at least Scandinavian researchers think is distinct about Scandinavia is worker independence. And it's something that I kind of wanted to just tease out a little bit in the beginning of this podcast. Am I wrong in this, or is there something distinct about the relationship between, I guess, workers and managers in Scandinavia, particularly? One speaks about the Scandinavian model. Can you outline a little bit what that means in manufacturing if it still exists? It's an open question.

JOHAN: From my perspective, Sweden usually ranks very high in innovation, also when it comes to international rankings. And I think some of that has to do with the openness and the freedom of thinking in a sense and not so hierarchical, more consensus-oriented, ability to test and check and experiment at work without getting repercussions from top management. And it is much easier.

In fact, if you are at one department in a manufacturing company or in university as such and you want to collaborate with another colleague across the aisle, if you have a two hierarchical system, you need to go three levels up in order to be able to do that. But here, I think it's easier to just walk across the aisle to have this collaboration and establish a cooperative environment. I think that that's part of the reason.

Also, we're not so many; I mean, I think historically, we needed to do a lot of things ourselves in Sweden. We were a country up north with not so many people, and we have harsh environments, and I think it's the same as Norway. I mean, you need to be self-sustainable in that sense, and that creates, I think, environmental collaboration.

TROND: We'll go more deeply into your research on manufacturing and to what extent a question I asked here matters to that. But do you have a sense just at the outset here that this type of worker and operators sort of independence, relative independence, perhaps compared to other regions, is it changing at all? Or is this kind of a feature that is a staple of Scandinavian culture and will be hard to change both for good and for bad?

JOHAN: I think that as everything...digitalization has sort of erased a lot of the cultural differences across the world in that sense. Because when I was a student, there was not this expressed digital environment, of course. The information environment was less complex. But I think now all the young people, as well as my mother, does her banking...she's 90, but she does her banking on her iPad; I mean, it's very well-spread.

And I think that we are all moving towards a similar culture, and the technology is spreading so quick. So you cannot really have cultural differences in that sense. But I think that's still the way that we're using this. And I think that the collaborative sense I think that that is still there. The reason why Sweden is comparatively innovative still is that we still maintain our culture and use the technology to augment that capability.

TROND: So, Johan, we'll talk about a bunch of your experiences because you obviously are based in Sweden. And because of Sweden's industrial situation, you have some examples, you know, Volvo, a world-famous company obviously, and also famous for its management practices, and its factory practices, we'll get into that. But you've also worked, and you're advising entities such as the World Economic Forum, and you are active on the European stage with the European Institute of Technology. Your activity clearly goes way, way beyond these borders.

But why don't we maybe start with some of these Scandinavian experiences and research projects that you've done maybe with Volvo? What is it with Volvo that captured people's attention early on? And what sort of experience and research have you done with Volvo?

JOHAN: I think that Volvo is very innovative, and Volvo today is two types of companies; one is the car company that has now gone fully electric. It was introduced at the stock market, most recently owned by a Chinese company, and before that, it was owned by Ford, and before that, it was also public. But you also have the other part, which is the Volvo Group, which is looking at trucks, and boats, and things like that.

And they both share a high level of innovation, ambition, innovation, and power, I think, using the experiences already from the '60s, where you had a lot of freedom as an employee. And also very good collaboration with the union in investments and in all the changes in the company I think that has been very beneficial. And it's made them...what is now Volvo Cars was very, very early, for example, with digital twins. They were experimenting with digital twins already in the 1990s.

And we work together with Volvo but also with SKF, which is a roller-bearing company here to look at how we can support frontline workers and augment their capabilities because they're very skilled and they're very experienced. But sometimes you need to have sensor input, and you need to have structures, and rules, and procedures, and instructions.

So we worked quite early with them already, maybe in 2009, 2010, to see how can we transform their work situation, provide them with work instructions through wearable devices. It was very popular at that time. MIT was experimenting with cyborgs. And the people that were...I think it was Thad Starner; he was trying to put on a lot of computer equipment. Then he went through the security at the airport and had some problems there. But that's not the case for the operators. But it was a little bit too early, I think.

We tried to experiment with some of the maintenance people at Volvo cars. And they were very interested in the technology, but the use for it was a little bit obscure. And this was at the time when you had the mobile connectivity was 9,600 kilobits through a mobile phone or in the modem, so Wi-Fi more or less did not exist. And the equipment: the batteries weighed two kilos, and the computer weighed one kilo. And then you had a headset that looked like you came from deployment in a war zone. So it was a little bit...it looked a little bit too spacy for them to be actually applicable.

And then some 10 years later, we actually did a similar experiment with SKF, the roller bearing company where we deployed the first iPod touch, I think they were called. That was right before the iPhone. I think it was an experiment by Steve Jobs to see how can we create what then became the iPhone screen. And we put that on the arms of the operators and tried to see how can we give them an overview of the process situation. So they were constantly aware, and they were quite happy about this.

And then, we wanted to finish the experiment. The operators actually said, "Well, we don't want to give the equipment back." And then we said, "Well, we need to have it back. Of course, you can use the software." So they brought their own phones, and they downloaded the software. And they're still using it, actually, not on their own phones anymore. But they use this kind of software that we developed at that time together with them. So that was quite interesting.

TROND: That's fascinating. Extrapolating from some of these early experiences up until now, I wanted to just ask you this from a research perspective, but also, I guess, from a management perspective. So you work on production systems. What is really the goal here, or what has the objective been early on? You talked about these early MIT experiments. And I know control systems is a very old area of research. And from what I understand, in the early days, the use cases weren't just factories; they were also on spacecraft and things.

But to your point, especially earlier, we were working with very, very different technology interfaces. But now, obviously, we are starting to roll out 5G, which gives a whole other type of richness. But does it really matter how rich the technology interface is? Or does it matter more what the objective is with these various types of augmentations that have been attempted really throughout the decades? Can you just give us a little sense of what researchers and yourself what you were trying to augment and how that depends or doesn't depend on the quality of technology?

JOHAN: First, we need to realize that the manufacturing industry has always been a very, very early adopter. The first computers were used for war simulations and for making propellers for submarines to see how you can program the milling machines. This was in the 1950s. And the industrial robots in the '60s in the '70s were also very early applications of digitalization. Before anything else had computers, the manufacturing industry was using it, and that's still the case. That might surprise some people. When they walk out into a shop floor, they see no computers around because all the computers are built into the machines already.

What is still missing is the link, perhaps to the people. So they are still using the screens. And they are the ones...people are the key components of handling complex and unforeseeable situations. So you need to provide them, I think...to be really productive, you need to provide the frontline staff with the equipment for them to avoid and to foresee and to handle unforeseen situations because that's what differs between the man and machine or a human and the machine.

People are much more apt to solve a complex situation that was not programmed before. That's the augmentation part here; how can we augment the human capabilities? And people talk about augmented reality; I mean, I don't think it's the reality that needs to be augmented; it's the human to be handling the reality that needs to be augmented.

TROND: Johan, this is so fascinating because, first of all, it's quite easy to dismiss manufacturing a little bit these days because, to the untrained eye, all the excitement is in the consumer space because that's where the new devices get released, and that's, obviously, where all the attention is these days unless you obviously are in manufacturing.

But can you bring us back to those early days of computing when a lot of the use cases for computing were first explored with manufacturing? So you talked about MIT, and back at MIT and at Stanford, all the way back to the '60s, they were exploring this new and fascinating field of even artificial intelligence, but before that, just regular control systems, electronic interfaces. What fork in the road would you say happened there? Because clearly, the fascination has been with digitalizing everything and software kind of one for 30 years, but in manufacturing, it's more complicated.

You say people, so it's people, and then it's kind of these production systems that you research. That's not the same as the use case of an individual with their phone, and they're sort of talking to people. There are many, many more variables in play here. What is the real difference?

JOHAN: Last year actually the European Commission put forth industry 5.0, which should be the follower after industry 4.0. And they based that on three main challenges. One is sustainability, one is resilience, and the various kinds of resilience towards the shock of the war but also by climate, et cetera. And the third one is actually human-centeredness to see how can we really fully deploy human capabilities in a society and also in industry, of course.

I think what you're referring to is the two guys at Stanford in the '60s; one was John McCarthy. He was the inventor of the artificial intelligence concept. His aim then was to replace human work. That was the ambition with the artificial intelligence because human work is not as productive as computing work, but it still has some drawbacks.

But in the same place not so far away, in another department at Stanford, was a guy called Douglas Engelbart. And he was actually the father of...he called it intelligence augmentation. So it was AI and IA at that time. But his ambition was to augment human work to see how can you have this. And he was the one that invented hypertext and the mouse. And he put up the first hypermedia set in Silicon Valley. So this was a guy that inspired companies like Apple, and Xerox PARC, those kinds of institutions that had a huge bearing.

There was a book by a research colleague at Oxford. He was comparing that over time, from the early industrial days and then forward, technology that replaces people always has more complications when introduced and scaled than technology that augments people. If you look at the acceptance and the adoption of the iPhone, that took months, or weeks, or whatever, seconds for some people, for me, for example.

If you look at what happened in the industrial revolutions in the 1800s and the 1700s, you had a lot of upheaval, and already in the 1960s...I'm starting to sound like a university professor. But in '96, in the U.S., there was a Senate hearing about is automation taking the jobs from people or not? And the conclusion was that it is not, it is actually creating companies that then employ more people because of the productivity gains and the innovation gains. And you allow people to use the automation as augmentation, not only cognitive augmentation.

We think a lot about augmentation as something that you do with your eyes and your brain. But robots are also augmenting people. It lifts heavy objects like cars or big containers, whatever. That's the kind of augmentation that maybe you don't consider when you look at it from an artificial or an augmented reality perspective.

TROND: Well, so many things to pick up here. But the variety of meanings of augmentation are kind of astounding, aren't they? And you've written about this operator 4.0 several times. There's obviously cognitive augmentation, and then there's physical augmentation. Are there other types of augmentation that you can speak of?

JOHAN: I really can't think of any.

TROND: But those are the main ones. So it's either kind of your mentality or sort of your knowledge. So the work instruction parts go to the skills-based, I guess, augmentation, which perhaps is an additional one. Or I'm just thinking if manufacturing wants to make progress in these things, it would perhaps make sense to really verify what workers at any moment actually themselves express that they need.

And I guess that's what I was fishing for a little bit here in this history of all of this, whether the technology developers at all moments really have a clear idea of what it is that the workers are saying themselves they're missing or that they obviously are missing. Because automation and augmentation, I mean, do you find them diametrically opposed, or are they merely complementary when it works well?

JOHAN: I mean, automation traditionally has been the way to scale, and, I mean, in the beginning, you want to see what the machine is doing, right? And then you really don't want to see it. You just want it to work. So it's really helping you to scale up your work. And in that sense, automation, like collaborative robots, for example, which people are talking about robots, are something that is replacing jobs, but if you look at it, it is a very small portion of statistics.

In Singapore, which is the highest user of robots installed, there were 950 maybe robots per 10,000 employees. And the average in the Americas is 100 robots per 10,000 employees, and that's not really a lot. And so there is plenty of space for robots to be the tools for people. So if you don't treat them as something that will replace you but something that will actually augment you, I think it would be much easier.

What could happen, though, and I think that is maybe part of your question, is that, well, these tools are becoming so complex that you cannot use them unless you increase your skill. How do you do that? Because no company would like to end up in a situation where the tools that you have bought and invested a lot of money in are too complex for your employees to use. That's a lost investment.

It's like you're building a big factory out in a very remote place, and you don't have enough electric power to run it. You don't want to end up in that situation. Like you expressed, I think that maybe what's missing and what's trending right now is that the upskilling of the workforce is becoming extremely important.

TROND: And how do you do that, Johan? Because there's obviously...there's now an increased attention on upskilling. But that doesn't mean that everyone has the solution for it. And employers are always asking for other people to pay for it, for example, governments, or the initiative of the worker, perhaps. It seems like Europe has taken this challenge head-on. Germany, at least, is recognized as a leader in workforce training. The U.S. is a latecomer to the game from that perspective. But it typically shows up in a big way. So something is going to happen here in the U.S. when it comes to workforce training.

What is the approach? I mean, there seems to be two approaches to me; one is to simplify the technology, so you need less training. And the other would be obviously an enormous reskilling effort that either is organized, perhaps ideally in the workplace itself, so it's not removed from the tasks. Or some enormous schooling effort that is highly efficient and perhaps online. What do you think are the winning approaches to re-skilling that entire manufacturing workforce continuously? Because it's not like you have to rescale them once, you have to rescale them every time.

JOHAN: Well, I can only guess. I think that you need to do all of these, all of the above. One complicating factor is the demographics of, especially Japan; of course, we know that from a long time that, they have an aging population. But Europe is now becoming the new Japan in that sense. We have a very big problem in terms of aging populations, especially countries like Italy and perhaps Germany but also in northern countries. And we don't have perhaps...there's a lot of discussion on immigration right now. But actually, the workforce would need a lot of immigration to be able to respond to the needs of our industry in the forthcoming situation.

I think that China is maybe 4 or 5 years behind Europe, and the U.S. is maybe 10-12 years behind Europe as well. So that will happen...the only non-affected regions right now are India and Africa. And that means that the European, and Chinese, and U.S. industries will have to compete with a rather young population in Africa and India. And so that will become over time, but it is a long time, so that means that it's not always on the political agenda. Things that take a long time are usually not the things that you speak about when you have election times that we have in Sweden right now. It's mostly what's on the table. So I think that how to do that is really complex.

We had some collaboration within the World Economic Forum. It is a fantastic organization because it spans the whole globe. So that means that the information comes from different parts of the world, and you can see different aspects of this. And a country that has done a lot about this is Singapore, very good experiments, very nice projects, initiatives regarding upskilling. And Europe is now launching an innovation program where they want to go deeper into deep tech to try to...the commissioner for research and education in June launched a big initiative around innovation and how that can be supported by deep technology. So we'll see what comes out of that. It'll be very, very interesting to see.

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TROND: Speaking about the World Economic Forum for a minute, Johan, you have been part of this group project called the Augmented Workforce Initiative. You told me when we spoke earlier that, in your opinion, this initiative couldn't have existed even just five years ago. Can you explain what you mean by that?

Because augmentation, the way that you've been speaking about it now, is a perspective that was nascent, even in the early days of computing and manufacturing control systems. Yet, it seems to have disappeared a little bit, at least from the top end of the political and research agenda. Yet here we are and you said this initiative couldn't have existed five years ago. Can you explain what you meant by that?

JOHAN: That is a very, very nice initiative by the World Economic Forum, and it's run by the forum and Cambridge University, who has a very, very good group on this and some very nice people. And I'm honored to be part of that group together with my colleague from Mexico, David Romero. You may know him as well.

And I think that what they're looking at is the increased understanding. And that was actually one of the sessions at this World Economic Forum, you know, the Davos days that were run this year. And it was actually part of those days as a theme about how to engage, and how to support, and to augment the workforce, which has never happened before on that level. So it's really, really high on the agenda.

The Forum has been running previous projects also on the future of work and how the demographic situation is affecting or how the skill situation is affecting the companies. They have come up with suggestions that more or less half the workforce needs to be upskilled within the next couple of years. And that's a huge undertaking.

TROND: The novelty here is that the world's elite managers, I guess, who are represented at the World Economic Forum are increasingly aware of the complexity of workforce issues generally, and then specifically of upskilling, and maybe even upskilling in this very specific meaning of augmenting a worker which, I guess to my mind, is a little bit different from just generally speaking about robotic automation and hammering these efficiency points.

But obviously, it's a much more challenging debate because it's one thing to find a budget for an automation effort and introduce a lot of computers or introduce a lot of whatever technology, usually hardware, but what we're talking about here is a lot more challenging because you need to tailor it to these workers. And there are many workers, obviously, so it's a complicated phenomenon. How is that going? What would you say are some of the findings of the Augmented Workforce Initiative?

JOHAN: I think that companies like Tulip, companies like Black & Decker, and others have a lot of good use cases actually already, which may or may not before have been labeled augmentation. It might have been labeled as operator support, or decision-making support, or things like that, or upskilling. But I think that the findings are that there is a lot out there, but it's not emphasized as something that is really important for the company's survival in that sense.

TROND: It wasn't so glorified before. A lot of the decision support systems were viewed as lower-level systems that were just kind of more like HR systems or just tinkering with necessary stuff that people had to know kind of a thing. And so you're saying it's been elevated now, yeah, as having a much more essential impact on the quality of work.

JOHAN: It has a leveraging impact for the whole company, I would say, but that's also part of this industry 4.0 approach. And you have the hierarchical integration of companies where the CEO should be aware of what's going on on the shop floor and vice versa, as well as the horizontal integration where you have the companies up and down the supply chain and value chain knowing what's going on early. And that is really something that maybe stopped at mid-management level before, but now it needs to be distributed out to the places where the complexity is higher, and that's the frontline workers.

Maybe...now I'm guessing, but I think that also the understanding that the investments done by this company in complex manufacturing equipment could be at risk if you don't have the right skills to use them is now penetrating, I think, a lot of the companies.

In Europe, in 2019 or something like that, there were almost 30 million people employed in the manufacturing industry. And if you look at the number of...if you say that half of these need to be upskilled somehow over a period of three years...and I actually made a mock calculation that the re-skilling need for in-person months in Europe if we were to fulfill this is 50 million person-months, 50 million person-months, just the time for the people to participate in these trainings. So that's a huge undertaking.

And I think that that scares companies as well as governments because just imagine taking 50 million person-months out of productivity or the production equation. But the alternative might be worse. If you lose your capability to use your equipment, that might even be worse.

TROND: Wow, these are daunting things. I guess that brings me to the last section here and some thoughts from you on the future outlook. When it comes to technology and these tools for human augmentation, what are the timelines for, well, either making the improvements or, as you said, not losing competitiveness because of this skills crisis? What are we looking at here? Is there some imminent challenge and opportunity? Or is this going to play out over 25 years?

JOHAN: I think that in 25 years, the demographic situations will have changed again, so I assume that they will look different. But right now, we have a problem with an aging population. And we have a lot of people going into retirement. A lot of knowledge will disappear unless we can store it somehow.

A lot of people will not go into industry. I mean, when I talk to colleagues, they say, "Well, we need to make the manufacturing industry more sexy. It should be cleaner, or it should be nicer because young people don't go to industry." But if I go to the healthcare section, they will say the same thing, "Oh, we need to make it much better because people are not applying for these educations."

TROND: [laughs] Where are people applying, the tech companies?

JOHAN: No, that's the problem. They don't exist. They were never born.

TROND: [laughs] Right.

JOHAN: So the demographic bomb is that they are actually not there. So you cannot rely on employing young people because they are not existing in Europe and soon not in the U.S. to the extent that they were before. So therefore, you need to focus on the older people. So you need to re-upskill not only the middle-aged people but the people in their 50s and even in their 60s. That adds to the complexity.

In the next 5 to 10 years, there will be a lot of discussions on how to fill the missing places in industry to remain competitive. I also think that you can see the augmentation here as a fantastic tool together with the upskilling because upskilling the new skills together with the augmented tools like collaborative robots, like cognitive support, like whatever you can put in an iPhone, or whatever phone, or tool, or watch, or whatever, you can add the capability to make decisions. And that's the augmentation you will see.

And you will see a lot of digital twins try to foresee problems. You will see a lot of transversal technologies going from different high-tech industry into manufacturing industry to support especially the frontline people and to enable their innovation capabilities.

TROND: Johan, you said earlier that the complexity is higher at the level of frontline workers. Did you mean that, basically, the complexity of frontline work of itself at an individual level is also underestimated? Or were you simply saying that because there are so many frontline workers and the various situations of various types of frontline workers is so different that it's obviously an underappreciated management challenge? Or were you truly saying that frontline work in and of itself is either complicated or becoming more complex?

JOHAN: If a task was not automated, it is inherently complex. So you couldn't automate it, right?

TROND: Right.

JOHAN: Because if you can teach a robot or whatever to do tasks, then it's not difficult, and you can foresee the results. There was a lady called Lisanne Bainbridge. She put out The Paradox of Automation that the more you automate, the more dependent you become on the few people that are still there to handle the situations that are so complex that you could not foresee them.

So everything that is programmed is programmed by a programmer, and the programmer tries to foresee every foreseeable situation, and to that extent, the robots and the automation works. But if these situations go out of hand, if they're too complex, and something happens, then there is no robot that can fix that. Unfortunately, AI is not there yet.

TROND: Well, you said, "Unfortunately, AI is not there yet," but I would also conjecture that, fortunately, AI is not there yet because you're pointing to something missing, I think. And a lot of the AI debate is starting to come back now. And it was there in the '60s because people realized that for lots of different reasons, to have a human oversight over robotic processes is actually a good thing.

And you talked to me earlier about the experiments with imagining a trip to Mars and having to execute robotic actions on Mars in a control system environment where you actually had to foresee the action and plan; it was always a supervised type of situation. So the supervisory control concept has been there from the beginning of computing. If you were to think of a future where AI actually does get more advanced, and a lot of people feel like that's imminent, maybe you and I don't, but in any case, let's imagine that it does become more advanced and becomes sort of a challenge, how do we maintain human control over those kinds of decisions?

I mean, there are researchers that have imagined, you know, famously in Superintelligence, Bostrom imagines this paperclip factory that goes amok and starts to optimize for producing paperclips, and everyone is suddenly producing, you know, and the machine then just reallocates resources to this enormously ridiculous task of producing only paper clips. It's a very memorable example. But a lot of people feel that AI could soon or at some point reach that level. How do we, as a failsafe, avoid that that becomes an issue? Or do you see it as such a far-fetched topic in manufacturing that it would be decades, if not centuries, away?

JOHAN: I think that AI has been seasonal if you allow the expression. There's talk about these AI winters every now and then, and they tend to come every 10 or 15 years, and that matches two Ph.D. lifetimes, Ph.D. development. I mean, people tend to forget the problems, and then they tend to use these Gartner curves. If you look at the Gartner curve, you have the expectation part. I'm not being arrogant towards the AI research. I think that AI is fantastic, but it should be seen, from my perspective, as what it is, as an advanced form of automation that can be used as an augmentation tool.

I think it was Kasparov that started to collaborate with a chess computer maker or developer, and they won every tournament because the combination of the human and the chess computer was astounding. And now I think there are even competitions with chess computers plus chess experts comes with them.

There was, I think, in the 1800s, there was a traveling exhibitionist where they had the Mechanical Turk, I think it was called. It was a chess player that was competing then against the people in the audience. And actually, inside this box, there was a small human that was making all the chess moves. And they were beating all the chess champions. So there was a man inside this. I think that there is still a man inside a lot of the automation.

TROND: A man and a woman. I wanted to just lastly end on a more positive note because you told me earlier that you are more optimistic now than ten years ago on behalf of your industry that you've researched for so many years. Why is that?

JOHAN: I think that the technology, I mean, I'm a techno-optimist. And I think that we have also the full scale, the full attention from the ICT industry on various industrial processes right now. It was a lot of service-oriented. And I think that that is playing out now in the platform wars, the different services, but these different services are actually making a lot of good in the manufacturing and the tougher industries. And so, there is a bigger focus now on creating CO2-less steel. And there's an exploration of different industries that are going across; you look at the electrification of vehicles which is cutting across several sectors in the industry, automotive industry, electronics industry.

And I think that the problems in industry are becoming so complex. So the ICT attention is on industry now more than perhaps on consumers, as it were, and I think that that's promising. I see companies like Ericsson promoting 5G. I see companies doing the Amazon Web Services and such companies looking at services that are useful for industry. And that's also augmenting the people's capability in that sense, so that's why I'm so positive.

I see all the sensors coming. I see all the computing power coming into the hands of the frontline operators. And I see also the use for the upskilling and the skilling technologies that are emerging. How do you do that? What they do in Matrix when the leading lady downloads the instructions for the helicopter or motorcycle or whatever it is. But how do you do that in real life? How do you prepare for something that's coming in the next few minutes? That is something that people are now looking at using technologies, augmenting technologies, digital twins, and things like that in a completely different way than they were five years ago.

TROND: Wow. So these are exciting moments for learning in manufacturing with perhaps wide-ranging consequences if we succeed. Johan, I thank you so much for these reflections. You've spent a career investigating production systems, and manufacturing, and workers. And these are very rich debates. And it seems like they're not over, Johan. So, hopefully, we'll have you back when something happens. And we'll have you comment on some developments. Thank you very much.

JOHAN: Thank you, Trond. Thank you for a very interesting discussion. You always learn a lot by being asked a lot of questions, so thank you so much for this learning experience. Thank you.

TROND: You're very gracious. Thank you, Johan.

You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim. The topic was a Scandinavian Perspective on Industrial Operator Independence. Our guest was Johan Stahre, Professor and Chair of Production Systems at Chalmers University of Sweden. In this conversation, we talked about how the field of human-centered automation has evolved.

My takeaway is that human-centered automation is the only kind of automation that we should be thinking about, and this is becoming more and more clear. Operators are fiercely independent, and so should they be. This is the only way they can spot problems on the shop floor, by combining human skills with automation in new ways augmenting workers. It seems the workforce does not so much need engagement as they need enablement. Fix that, and a lot can happen. Thanks for listening.

If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and rate us with five stars. If you liked this episode, you might also like Episode 84 on The Evolution of Lean with Professor Torbjørn Netland from ETH Zürich. Hopefully, you'll find something awesome in these or in other episodes and if so, do let us know by messaging us. We would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects people, machines, devices, and systems in a production or logistics process in a physical location. Tulip is democratizing technology and empowering those closest to operations to solve problems. Tulip is also hiring, and you can find Tulip at tulip.co.

Please share this show with colleagues who care about where industry and especially about where industrial tech is heading. To find us on social media is easy; we are Augmented Pod on LinkedIn and Twitter and Augmented Podcast on Facebook and YouTube.

Augmented — industrial conversations that matter. See you next time.

Special Guest: Johan Stahre.

Episode 100: Innovating Across the Manufacturing Supply Chain

Tulip — Wed, 19 Oct 2022 00:00:00 -0400

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is Innovating Across the Manufacturing Supply Chain. Our guest is Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker.

In this conversation, we talk about lean leadership, productivity, the challenge of digital transformation across operations and supply chains, and how augmented lean means every organization has their own transformation approach.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 94 on Digitized Supply Chain with insights from Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Stanley Black & Decker is a huge organization where any improvements by tweaking their own operations or by adding insight from what happens along the whole supply chain can mean significant productivity gains. I find it interesting that they have their own version of the augmented lean approach tailored to where they are and, most importantly, building on the insight that the workforce is where the innovation comes from. By giving shop floor workers access to insights on big-picture manager deliberations, they are freed up to operate not only more efficiently but also more autonomously. When all of industry works that way, manufacturing will make tremendous advances more rapidly and sustainably than ever before.

Transcript:

Augmented is a podcast for industrial leaders, process engineers, and shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Antonio, welcome to the podcast. How are you?

ANTONIO: I'm good. How are you doing?

TROND: I'm doing great. I'm looking forward to thinking and talking about manufacturing supply chains and the rollout of digital technology. So, Antonio, you are actually a business major by origin from North Texas, and then your master's is in HR. And then you're fashioning yourself as a lean leader and an operational expert working on productivity and now much on digital transformation. And you're heading the rollout of digital solutions for Stanley Black & Decker. I'm curious, what was it that brought a business major into the manufacturing field?

ANTONIO: For me personally, businesses is great. I'm a big advocate of free markets. And so for me, the whole time you think of how widgets are created and wanting to understand that aspect in manufacturing, creating widgets. Like you were saying, with a master's in human resource development, my thoughts there were learning that a lot of the cost from any organization is going to be labor and material. So having that understanding was great.

And then transitioning to making widgets and learning under some ultimate awesome leaders in the space along with great engineers that really, really, hand in hand taught me so many things. And then one of the leaders in lean as well having hands-on conversations, walking the site with this person that is known for lean just really, really strengthened my capabilities. But the thought of the digital side is always going to come into our space, in our world. And so to be able to do that for a large fortune 500 company is obviously amazing. I'm like a kid in the candy store.

TROND: [laughs]

ANTONIO: Those concepts really changed the way from an organizational side because business is business no matter how you look at it. We're trying to improve our margins and capture market share just like anyone else. But ultimately, it's just a different way of doing it.

TROND: I wanted to stop a little around lean first because in our pre-conversation you said lean touches everything. I'm just curious, what do you see as the key things in lean that you have learned that you are bringing into this work that we're going to be talking about a little bit?

ANTONIO: I think that it boils down to a way to create continuous improvement by impacting ultimately the lead time. I'm part of the global supply chain so obviously, I'm always looking at a holistic approach. That's why it's all aspects for me from a business standpoint. At the same rate, from a lean perspective, we can find waste in anything. So there are always opportunities to improve in that aspect in every single function.

Every function within the organization can be an aspect of lean. So that's the part for me that I get excited about, and I've touched every single function. So it's really an opportunity for any organization to continuously improve on and removing what they say muda from the origination of the concept in any organization.

TROND: I'm curious; some people would say that lean is or I guess was important early on but that contemporary organizations are somehow different, and digital, which we'll talk about, is one reason, but there are perhaps other things. What are some of the things that you, I mean, I don't know if you agree with this, but what are some of the things that you're incorporating into your thinking here that may be either different or where you have to adjust it to the organization you're actually in at any given moment? I'm just curious.

ANTONIO: You're thinking lean from a digital standpoint or just lean?

TROND: Well, lean was developed in its original form a very long time ago. So I guess the first question I'm asking is how can you be confident that the original insights are still valid? Is that because you're walking around and experiencing it every day, and it resonates with you? I guess, firstly, just curious about what lean generally means today in an organization like yours, and then obviously, we'll talk about the rollout of digital solutions, which you've been doing so much now.

ANTONIO: Right. And that's a great question, and I'm excited to be the person that has to answer that question.

TROND: [laughs] Well, you didn't think I was going to give you easy questions, Antonio. [laughs]

ANTONIO: Lean, the concept, I think, will never go away. And so for those that think that it will, really do not understand engineering from that standpoint because when you think about engineering, an engineer solves problems. And so we know number one, there's always going to be problems. I'm sure that there are a lot of people that say, "Hey, I got something for you to solve. I got a problem for you," so from that perspective, we know.

But then, on top of that, think about innovation from an engineering standpoint, as you see something improved, even if it's making it better, even if it's something like making it better for the customer, ultimately, that transition of change even the slightest or something large, every organization has to do it. They have to embrace it. And so a person that knows those techniques, that are really good and seasoned and experienced, which I would say I do fit in that; I feel mighty confident in that space, and I feel mighty confident in manufacturing, we could see it quickly. You see it immediately.

Like, you see a process, and it just stands out. And I think that you can't wish that away to be able to see the inefficiencies of any system. And if you do not have a system in your approach, then that to me is already folly, you know what I mean? Like, that's an error. If you can't create systems, especially in manufacturing, I think that that's no bueno.

[laughter]

TROND: Got it. I'm then curious, digital. How does digital factor into all of this? So I guess I'm understanding a little bit more of your conception of continuous improvement, lean, whatever you really want to call it, and engineers that are such a crucial part of the kind of organization you represent, Stanley Black & Decker.

So now, clearly, there's been a push in most organizations across fields to go digital and arguably, manufacturing organizations perhaps were resisting it a little bit because there was such an amount of automation in there already, and then now comes digital on top of that. And has it been easy? Has it been difficult? What goes into even the decision to say, "We're going to have a major digital transformation?" Tell me a little bit about the journey that you've gone through with Stanley in that respect.

ANTONIO: So, really great question. And so I'm going to take you down a little bit of a history lesson and introduce how it impacts. So when you think about things of the world, because you always have to relate to what's going on in the real world, you have the introduction of the smartphone. You have to credit that smartphone for that interaction of this interface because it's putting that into a lot of operators' hands to interface with something.

Now, when you think about digital, industry 4.0 touches a lot of things; it's very vast, very broad. But when you think about the insights and paper throughout your organization that's there but being able to in manufacturing...and I'll make this a little bit specific to manufacturers. There are so many points where you actually need data to improve throughout that process, and like I said, it's a system. And so if you can capture it in a digital way, now you can analyze it. Now it's an insight. Now you can take all of this, and you can do predictive analysis. You can add algorithms, AI, whatever you want once it's digital.

And it's transforming your operation to be able to enhance it in this digital way so you can advance and be a little bit more productive and get better, and so it still comes back to lean. [chuckles] Once you've created it digital, now it's like, what am I going to do with the data? Because you can do the wrong things with data. It can give you the wrong insight. And just making those decisions of where you are going to improve, I think that is really huge.

So for me, that transition starts with realizing the digital side, removing some of the paper. I mean, there are so many people that are old school I would say that do everything with paper. And if that paper was digital, then what could be? I'm smiling now because it gets me excited because there are so many processes that are old that people just pull out a paper and they use it even though we're in this digital age.

TROND: So I thought I would then move us a little bit into the aspect of having a digital platform. So digital means a lot of different things to different people. You say having access to digital gives us options basically because then you have data, but you have to do the right thing with it. First off, what kind of a decision and who was involved, I guess, in the decision at Stanley going digital in that sense? Because there are many different echelons of an organization that could potentially use data.

Who was the most excited, I guess, to use new data in your organization? How did that even come about? Was it a leadership decision? Was it mid-level managers that said, "Other organizations, our peers have more data?" Or was it analyzing, you know, Gemba Walks and walking around and saying, "Hey, the operators could be more productive with more data?" Where did the decision point come from?

ANTONIO: To answer your question, short answer would be leadership. We're pushing for the next edge in innovation and pushing forward to create change. And then it's what can be that thought, and I would say the collective. If you were to embrace true employee engagement and start from the shop floor, it's going to be things that they don't know that they're requesting, something digital, so to speak. They're just saying, "Hey, this would be cool. This is what I need in order to do my job effectively."

And then what about the supervisors to the middle managers that are trying to share insight of it's great to say that you hit your numbers or you produced your widget in a successful time or faster than you anticipated, but what about the opposite? What about when you did not meet your numbers? Being able to speak to that with data that's a huge win. Who wouldn't want that? And there are a lot of areas that are little dark areas in a manufacturing facility that you don't have that capability. And that's why you need some type of way to be able to shed light on those areas and capture that in a very effective way.

TROND: Tell us a little bit about the digital rollout process at Stanley. What went into it, and what is the situation? What sort of systems have you opted for, and how are you rolling them out?

ANTONIO: So within our organization, everything comes out with governance so thinking of and a way of controlling exactly what's completed, what's being done, what you are going to put within the facility, and then creating some type of uniformity around that. The interesting thing about our organization is we're a huge conglomerate. We produce many different parts and units. And it's just a lot of complexity and diversity as far as the people are diverse, but I'm just saying end product.

Manufacturing facilities...I'm global, so I'm facing all over the world different processes that we do and so being able to have a very tactic way to roll that out in a uniform way. That's really the strat there, really thinking it out. But then also allowing for those unique scenarios to come about, having what we call citizen developers. It's that employee engagement part, thinking about someone that's really close to the process. They may figure out a way that, hey, we need this type of solution, listening to them.

And then the fact, like I said, I'm global, I'm seeing way more than they are. And I can be like, and our team can look and say, "Hey, this actually could be used at several sites that look just like this one." And so we can get that MVP and create it in a very standard, uniform way so then we can roll it out on an enterprise level. And so all of this together is the way that we go about rolling out digital solutions.

TROND: So, Antonio, I'm curious about this because in classical automation, usually, it's a big sunk cost, and the system is stable, perhaps, but everyone has to learn it and do it one way. Is the current wave of digital transformation that you're talking about here does it allow for both strong governance, which you clearly need in a large organization, but also for those citizen developers to emerge with their more kind of not exactly bottom-up, but they are certainly factory-based, or they are site-based perhaps innovations?

Did you have to choose technologies that allowed for that, or how did that factor in? Because classic solutions of automation is like one size fits all, but you seem to be talking about, yes, the need for governance, but there's also the need for citizen developers. How did you enable those citizen developers?

ANTONIO: So the first thing is that you need to figure out something that's adaptable. And so for us, we use something zero code, so it's really, really easy for them to use. And so the thing is that you don't want to discourage innovation at all. You want to embrace employee engagement all that you can. At the same rate, there's another team that's going to make sure that cybersecurity and all of that that I'm playing within the confines and the rules, and if I do not, then definitely there'll be a discussion about it.

And so understanding that you're really balancing both, and you're controlling that citizen developer as much as you possibly can, being aware of what that individual may do. And at the same rate, watching and being able to take away their permissions if need be if we feel that it goes into...I don't want to say a danger, but it's not good from a governance standpoint of what they're doing due to some federal regulation or law or whatever have you. So it's just the balance of the two of having a platform that can give you that adaptability in order to control.

TROND: Antonio, can you expand a little bit on innovation? Again, in the context of a workplace that is becoming more and more automated, how do you inspire innovation? What does it mean for Stanley, innovation?

ANTONIO: When you think about what can be...let me give you an example of something that we created; I think that it will shed light. Every organization they go through physical inventory. So you have to count all your inventory and make sure that what your books say [laughs] that's what you have. It's just comparing those two from a financial standpoint. So you're going through that process.

And normally, this process is very manual where you're physically going; someone is sending out, making that count, writing on a sheet of paper of what they were able to capture, and then running that sheet of paper to some control room where everyone is conducting...basically calculating where you are now. And so everything's live. So you go, and you audit that area, and they come back.

So basically, someone is running around facilities. And if you look at some of our facilities, they're pretty ginormous, pretty big. So to go to one end to the other it's going to be a hike. And this is all on physical paper for the most part. This is all live, speed. So the thought came up when you say innovation, someone was like, "Is there a way to do this digitally? Why can't we do this digitally?" Just to speed things up, just to figure out, hey, where are we right now? Instead of getting all of these sheets of paper and then typing them again in some system.

And I go back to lean. That's rework. That's overprocessing. Even within this system, rework is someone already wrote it down on a sheet of paper. Now they're going to hand it to someone else to literally type it into another system. That redundancy can be removed. So you see that there is an opportunity there to save time because no one wins when we're doing a physical inventory. The site is shut down, and we're not making widgets. So you don't want that.

So anyway, there was a person that was like, "Hey, can we do this digital? There's an opportunity." So that's the innovation there. It starts with an idea and then sharing that idea saying, "Hey, is this possible? What can be? What is possible?" And then you have a very diverse team look at it along with accepting that idea. And you transform it into an application in order to conduct physical inventory. And we did just that, and it was huge.

And obviously, it's within, like I was saying, you get that MVP. And now we can just copy and paste that across the board to different sites and use it as much as we want from that standpoint with those same winnings, those same gains, and the same objective in order to help the site and use as much waste that is normally committed in a physical inventory.

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TROND: Antonio, you speak of apps. What are those apps that you speak about here, and how do you explain the concept of an app, I guess, to your operators? Because I'm assuming there is a bit of an educational journey there, too, when you're introducing certain new digital processes going, like you said, in a basic sense from paper to digital. And then you said it comes through these apps.

How do you explain the concept of apps, and how do they materialize, I guess, on the shop floor? I mean, they clearly are created. Are they created mostly by the vendors that you contract with, or are they created by your own engineers? Or are they created factory specifically, or how does this app development work? And what is an app?

ANTONIO: So they're created by our engineers. And this is actually pretty funny that you asked me what an app is. And so that thought is really important because this is something that we have to do out there on the floor. And so when approached with someone that you want to use this application, I don't think that I ever even say the word app to an operator as I have physically trained operators on an application. And it's just more so the process of what you would like them to do.

And one of the reasons of perfection, so to speak, is what you strive to do when it comes to the user interface and the user experience. You want to make the least amount of steps. You want to do the least amount to interfere with this individual that has a really, really important job to make widgets. And so the thought here is the explanation of what you're trying to accomplish and then the steps that they need to do to interact.

And like I said, what helps is obviously smartphones, you know, everyone's interacting with it. So, in our times today, I think that it's a little bit easier. If you were to take it maybe 15 years ahead, maybe it'd be a little bit more challenging, but I would say that not everyone is ready for that change. It's still new to them despite smartphones being there saying, "Hey, I have to interface with this iPad or a tablet, or touch screen," whatever have you; however, they're interacting.

So the ideal state is to create it where it's more automated. And so the application is just kind of like, it's a matter of fact. We're capturing all this data, and you're just doing your job. And we're just using triggers to be able to indicate what you're doing. So that's really how I would go about describing an app, never really saying app and just saying, "Hey, this is a process that we would like to use as you do your job really."

TROND: Antonio, would you speak specifically about Tulip as a digital solution? And what is that being used for, and how is that being rolled out? I mean, to the extent you can go into some detail, what is that platform doing for Stanley?

ANTONIO: For us, using Tulip is really, really advantageous because there are a few things that it's really, really great at. You can create pretty much what you want. I don't want to put it too much out there. And the easiest way where you don't...I mean, I have software engineers that work for me. But you don't have to be a software engineer; you could be just anyone. So that part makes it a great deal simple and then what it's capable of connecting to. So it can just easily integrate within your organization in order to achieve some of the things that you want to achieve, so from the standpoint of hey, we just need this very simplistic way of doing this.

And then what's more important? The UI. So it's like, what do you want this interface to look like and do? Because sometimes, I don't want to speak specifically to some organization or tool, but some tools that you can use make it very challenging with the user interface where it's just too much buttons or too difficult to get to what you want to. Versus, you have with Tulip a little bit more autonomy to make it and cater it to what needs to happen, where you've leaned out a lot of it and just say, hey, just come touch this button and do this, and that's it.

Because you want to make it simplistic, but maybe there's something else and another look, another view that you want to use. And so, using the same platform, you can make a view for someone else that will be looking at that data in a different way. And so that's the cool thing is it's all on one platform. So that makes it a little bit more powerful that from an operator standpoint, you've given them what they need, very simplistic, the limited amount of buttons. And then, for a different audience of a managerial role, you've given them the insights that will help to improve productivity within the shop floor.

TROND: What are some of the use cases that you then identified so far and are rolling out in these kinds of apps on that platform? And what are some of the things that one might think of? Or is that more of an iterative process that it's like, can you even map that out a year ahead where it's going to be used? Or is that like it's such an iterative process that it will evolve more organically? But either way, where's the starting point? What kinds of things have you now digitized this way?

ANTONIO: Within every manufacturing facility, they're going to say safety is first, and Stanley Black & Decker is no different. I can tell you what number one is, what 1A and 1B it’s...I can't say the other one is 2. So 1A is going to be safety, 1B will be quality. And so the difference here...and I want to differentiate something really quick because it's very important.

Being able to identify from the factory floor what's going on this is something totally different. From the operator's point of view and the data that they can create, that's different. Looking at other things is interesting, but what actually goes on on the manufacturing facility shop floor that type of data that's where it's important.

And so, to your question, you can, for instance, audit something. You can audit a process. That's something that's very, very easy. And you can do it in both realms. You can audit a process for safety. You can audit a process for quality. Those are two examples there. And obviously, you can advance that even more as you touch the product that you're making. And then once you touch the product that you're making, now you can relate that. That's where my business side comes in. Now I can take this beyond from a holistic approach.

So for me being global supply chain, this one place where it was touch, I can go backwards. So I can go further upstream to the vendor, to the site, to any other buffer in between that, let's say a distribution center, to the customer, back from the customer, and then a thread that goes all the way through. The insights are endless, and the capability and possibilities are endless when you can capture it all at the shop floor.

So that's really what we aim to do, really lighting up those dark spots and getting as much with the operator. And that's why operators, I mean, what's going on in our world and not just Stanley Black & Decker, as automation and digitizing the factory floor, this is going to definitely augment and amplify shop floor workers in a different way. And it's going to be really, really advantageous for you to be alongside that operator and enhance their skills to be able to be within a manufacturing facility to change because it's obviously changing. But you can make it where they're advantageous to the organization of what they do and give them a little bit more skill set.

It's almost like giving them more information, like going to university, so to speak, because they're able to see what they know. But now that cognitive data, we can take it from them digitally, and so now you can do more. You don't have to be thinking about that. It's like, oh yeah, we'll capture all that. Let's put something else on you. Because we'll take that cognitive data and store it for point solutions later on and now if need be. So it's a very interesting time within manufacturing of where we are now and what I foresee in the next 5, 10 years.

TROND: Do you think that manufacturing shop floors have trusted operators enough? Or was it just that the opportunity now of seeing more of the big picture is only now being realized with these digital apps so that this information is there and then you can trust them more? But it was interesting to me. I just want you to talk a little bit more about the new role of shop floor people, basically, that are now perhaps able to take on different things because of this new set of information that's being tracked.

ANTONIO: So when you really think about the frontlines, I would love to say and sit here and talk about how great I am and what I do for the organization. Oh, I think of all of these ideas. But for our organization and probably any organization, it's the people that make the widgets that are the most important people within the organization I would say. They're the workers, and the knowledge that they have of that process is so important.

At the same rate, we would say that the majority of those workers do not have fancy degrees or anything like that. And so we tend to think that possibly...well, I don't want to say that we tend to think that. It talks about the capability of what they're capable of, and so now with this, and if you can do it in a way for a digital transition, you can now look at what those capabilities are, the insight that they have. Okay, you do understand this process, then what's next? How do we improve it from a lean standpoint?

But you also intricately know, let's say, for instance, this machine you work on it every single day. But now we're going to create a way where you don't have to work so much on your, like I was saying, the things that you think about. We'll create something to do that for you. Now we would like for you to do something else. You see how this change comes up. We need you to just do this or that. And I don't want to be specific, but that's really how the change is occurring.

And to be honest with you, it's a huge win because there are many operators that actually enjoy...they want you to know and understand the data of what they do. It changes things because it can be a very technical job within manufacturing where you pull out a drawing. There's a certain specification that you have to hit, and that's going to make a difference if that part is manufacturable or not. And we're talking about sometimes you're pulling out calipers to get it within 2000s where it's got to be exact. It's almost like an exact science. That grace invariant is not that much.

And so, to be able to record that data digitally and view it that way, the operators are all for that because it helps to explain things that maybe they can't put into words, but the data will show it. And it's just like, "You see? You see what I'm saying? Right about this time at 4:00 o'clock, this machine always does this," I'm just giving an example. But you can see that from a data standpoint, and that will help the operator as far as transition into this new manufacturing operator, I believe.

TROND: So, Antonio, I think I'm now understanding a bit more about how this works on a given factory floor. Can you help me understand more about how this works all across the supply chain, which you were talking about earlier? Because now, I'm assuming the use case for you is not just one individual operator or sets of operators and teams doing one product in one location. You're talking about coordinating this across a larger supply chain. Now, how can these apps then come into play? Because now we're talking about different geographies, a lot of different contextual information that would need to be put into place.

How do these apps truly help smooth out the supply chain? It would seem to be a much perhaps more complicated challenge than just simply making an individual worker or team's life easier with safety and quality with precise work instructions. When you're talking supply chain, what do you really mean there? And what are the first, I guess, apps that are coming out that are going to truly impact the full supply chain?

ANTONIO: So know this, [laughs] it's like...I'm going to give an analogy because I want to make sure that you can understand because it can get really advanced when looking at things, so hear this out. So think about those pictures where you have the picture, and everything has a number. And so you go you're number one, and let's say number one is blue. So you fill in all the blue. And then number two is yellow or whatever. At the end, it's going to be a picture that you see, and you can recognize, oh my God, a parrot, when you're at the end.

So the way that the approach here is is that we know that it's a parrot. We understand that. And so the other functions within our organization know that it's a parrot, and maybe they're only focused on the blue, but they know that it's a parrot. And so, having certain datasets will fill in the blanks for them. Something that didn't have color now has more color, so they can make more of an informed decision on what they do because everything is connected. You cannot get away from the other.

So everything really starts where you make the widget, I think. It doesn't necessarily start there because you got to get the supplies to be able to make it. But what I'm saying is is that's the money time. But at the end of the day...and I'm going to go back to what I said earlier of how I summed up lean. Everything is lead time.

So I'll give you another analogy. I love kombuchas. When I go to the store, there's a certain kombucha that I want, and when it's not on the shelf, I'm going to go somewhere and get that kombucha. I'm not going to keep going to that store. And so, at the end of the day, this is the type of data that's needed throughout the whole global supply chain in order to ensure that our customer has that kombucha, so to speak. And all of that data insight is imperative to not only understand it but be able to do magic with it, so to speak, and make changes to continuously improve.

TROND: Interesting. As you're thinking about how these developments are affecting the future outlook in the manufacturing industry, or for your company, or maybe even wider for society, because some of these things, when they're compounded they, could have perhaps larger impact, what are some of the things that you think is going to come out of this in a 3 to 7 or 10-year timeframe? You've talked about shop floor operators becoming something even more special, perhaps. So I'm assuming that's one thing.

And then, if you want to think maybe about the larger workforce, what are some things that this will lead to? And then, finally, we just talked about the supply chain. Thinking ahead, what is likely to change when this has permeated throughout many organizations' supply chains with a lot more information available? What are the potentials here? What are the impacts?

ANTONIO: The main thing I think that will happen, and I think that it's already happening, is there will be a through thread through all the functions. I think that that's imperative. But I think that it will be a little bit easier with data. So the latter of those three that you was talking about from the future standpoint, I think that the through thread with that data as we advance and make even better applications for the shop floor to get even more data, you will be able to take that data to other functions to make changes, to improve, and reduce costs within your organization all across the board. So that's where the future will lead.

The former part of the question, as far as the change of the shop floor worker, I believe that from my perspective, I think that the world is changing. Education is changing. The cost of education is changing. And I think that from the older workforce, not to put an age on it, and what manufacturing was in the past is adapting. And the type of worker that is within a facility is different than it was because the people are different. We think different. We have Twitter, and Instagram, and Snapchat.

And so I'm throwing these things out here just saying, hey, we have a different workforce. They think different. And so I believe that manufacturers are adapting to this different workforce, and with that will come much change and much-needed change. And the capability of what a worker is expected to do, I think, will increase, but it will increase for the better. There are different roles for individuals to have within manufacturing facilities, and I think that we'll see that just come over time because we need data.

Data is going to be very, very important for any organization, and how we obtain that data, how we get that data, it's just better to have that person in the room having a big impact. And I'm saying that person, that operator in the room without having them in the room, so to speak, by getting their data to impact those decisions in their own way, but also using employee engagement with the data that they provide. So I think that's going to be really the change.

I think the number two question I kind of forgot. I apologize. I went from the last to the first.

TROND: No, it's fine. I mean, I was talking about the operators and then the advanced supply chains, which is, I guess, just another layer of complexity, and we have talked about it at length. But I'm just wondering, as these technologies, the digitization really advances and permeates throughout the supply chains, what are some of the cascading changes or not that might occur?

Because I'm assuming, just like you said, shop floor operators will have a different reality. They can do different things because some things are just taken care of or the beans are counted. They can do other things. What are those other things that organizations now can do because their supply chains will become more and more digitized?

ANTONIO: Yeah, those things are really...when you think about the footprint of what a facility needs to be, now that changes. Because one thing that's really, really important in any facility is space, so now this will impact it. Hey, we got this covered; could you go take care of these things? And then also I believe, so this is just going to be my opinion, I think that there's going to be more training. Now we can train up in another skill set to allow someone to have dual if not triple capability within their self to do more.

Let me tell you a little bit more about this machine because what we needed you for we good on that. Let's teach you about this other aspect of this machine in order to make it, you know, the upkeep of it, the PMs and TPMS, you know it. We've automated that and made it digital, but let's advance your knowledge a little bit more so you can understand. And I think that that's what we're about to witness here as we move forward.

To me, it's a really, really beautiful time. And it's going to be really, really interesting here in the next I would say ten would be the keymark, 5, especially with the climate today. And not to speak about the elephant in the room, but it truly is the perfect storm, all of these things happening. Like, going into a supply recession and then possibly having demand to drop, I mean, it's just a perfect storm of all of these things. But you'll see that those that are able to survive this will be better off because of it.

You never wish these things to happen. But you can say that you will improve, and you'll be stronger because it happened. And this also will impact what's needed in the future, especially on an operator level. So it's really interesting where we are today and how digitization will impact our lives and manufacturing from here on out. There won't be a point where it's not there. It will always exist for quite a bit of time unless there's some drastic change or an invention of some sort.

TROND: Antonio, the last question I'm going to just throw at you is, what are the training consequences? And how do you see training going forward in the medium-term future? Because you have pointed out that shop floor operators are going to be asked to do more things, more advanced things. They will get more of a bigger-picture view.

You're going to need a lot of true engineers, and then you might need a lot of engineers, meaning their engineering like they are trained with a mindset of an engineer in the sense that they are trained on improving, and suggesting, and tweaking, and adjusting the way that an engineer did. But surely, all of these people can't go to engineering school.

ANTONIO: [laughs]

TROND: How are you going to do this? Because the way I'm seeing you painting the picture of an emerging manufacturing workforce here, I mean, unless you're not talking about the same people, how are those same people going to adjust to this new reality?

ANTONIO: Right, yeah.

TROND: Is the UI going to be the key here, the UI just has to be simple the way you've explained that apps have to be kept simple so that training is limited? Or are you foreseeing that complexity still will increase so that people are going to have to become trained on still sophisticated piece of equipment? Because it could go two ways here, either you're doing advanced things, but you're keeping it simple still, or you're doing advanced things, and it's complicated. [laughs]

ANTONIO: So this is a great question, and I'm really excited to answer it. So the thought here is is, I'm going to take a CNC, a computerized numeric control machine. That is a very sophisticated piece of equipment, and an operator runs it already. No matter what they do, they're already running it, and so they're capable. And yes, they didn't go and get this advanced engineering, and those that receive those advanced engineering degrees they're worth every penny. It's teaching you on a vast scale.

But in a manufacturing facility, on what you're doing, you're removing some of the noise and saying, hey, I just need you to learn this. This is this process. So just this, just eat what's on your plate. Don't worry about any of this other stuff. And we'll guide you through. We will layer on, and layer on, and layer on the knowledge that we want you to have in order to enhance you on this process. And this process is core to manufacturing. See how that sounds a little bit different?

Because when you go and get your degree, I'm just going to pick engineering, you're learning all types of things, and they're all important. And there's a lot of physics and just a lot of things that you need to understand. At the end of the day, if you were to take an engineer off the streets that just got their degree and throw them in, how different would they be if you had a seasoned, experienced operator that knows this process and you compare the two? That would be an interesting comparison. I actually would like to see a study on that.

I think that, not to get deep, I just think that there would be a point where if you were to graph it where they would intersect, and that person with the advanced engineering would supersede this operator. But how long that would be would be interesting if you've created an environment and a very easy way through applications and digital solutions to improve this operator where they have knowledge and a different way of explaining it to them, all of these things where you've advanced and upped one. Like, you've upped this operator to this process. I think that would be interesting.

I think that that's going to be the future. You're going to have core competencies of manufacturing operators where they can feel proud. Despite that, they would be labeled blue-collar; I believe that their skill set and their knowledge would be probably more than what their label of blue-collar will be because they will be strategically very important to that manufacturing facility because of the knowledge that they know about that core competency of the process. And then just think about this, you learn one, you can learn something else. [chuckles] You know what I mean? And so I think that it just continues. So that's the way that I see it playing out.

TROND: Antonio, I think, to me at least, when I listen to this, it feels inspiring. And it certainly should feel inspiring to whether they are younger or older people who are interested in manufacturing because this spells a day and age where perhaps yet again, this kind of insight of knowing how to work machines and knowing how to coordinate with others on a shop floor or producing something tangible is going to be re-appreciated the way it was in other types of industrial upheavals and revolutions.

It's interesting to me that this is perhaps where we are, this inflection point where the kind of skill sets this will take and perhaps the kind of specialization that now seems perhaps within reach for a different cadre of people. Because clearly, MIT and, Carnegie Mellon, and UCL would have to scale up their training or offer everything they have for free online in order to train 10x, 100x, 1,000x more engineers.

Or these skills are just going to have to be taught in a combination of community colleges; I would assume, and on the shop floor directly by yourselves in these organizations themselves or perhaps a mix of the above. But either way, it would seem to me that it's not all that bleak of a future for manufacturing if what you're saying comes to --

ANTONIO: Fruition.

TROND: Fruition here.

ANTONIO: I agree. And this is really what I see, and that's why I'm excited. I'm happy to be a part of it. And it's one of those things...someone said this to me the other day "Industry 5.0." [laughs] I'm just like, okay. You can hear that concept, but from a societal standpoint and a person that is an advocate of free markets, I think that this is the moment in time in our world because we have to make widgets where we'll define what that is.

And before we talk about this industry 5.0 talk, the human part has to be addressed. And if you do it in the way that we're discussing, it makes for an interesting future. If you do it and bring other things into the discussion room already, I think that it changes basically what's being spoken about and not really discussing, okay, what is really going to move the needle and move us forward as a manufacturing group together? Because we compete against each other in some realms if we're in the same market, but it's all the same game no matter where you are.

And you're taking this from a guy that they would put in the plane and drop in a facility and now have to go through and just figure things out and could actually make change. But one of the things that I recognized everywhere I went in all the facilities that I've been to, all the facilities that I visited, were the people. The people were the important aspect. And you just definitely want to make sure that they're in the equation and in the dialogue of whatever change may happen. And I believe that platforms that allow that will be key for now and the future.

TROND: Antonio, you've been very generous with me, your time. It's been super interesting. Thank you so much.

ANTONIO: Thank you. I appreciate it.

TROND: You have just listened to another episode of the Augmented Podcast with host Trond Arne Undheim.

The topic was Innovating Across the Manufacturing Supply Chain. Our guest was Antonio Hill, Head of Manufacturing Digital Solutions, Global Supply Chain at Stanley Black & Decker. In this conversation, we talked about Lean leadership, productivity, and the challenge of digital transformation across operations and supply chains.

My takeaway is that Stanley Black & Decker is a huge organization where any improvements by tweaking their own operations or by adding insight from what happens along the whole supply chain can mean significant productivity gains. I find it interesting that they have their own version of the augmented lean approach tailored to where they are and, most importantly, building on the insight that the workforce is where the innovation comes from. By giving shop floor workers access to insights on big-picture manager deliberations, they are freed up to operate not only more efficiently but also more autonomously. When all of industry works that way, manufacturing will make tremendous advances more rapidly and sustainably than ever before. Thanks for listening.

If you liked the show, subscribe at augmentedpodcast.co or in your preferred podcast player, and please rate us with five stars. If you liked this episode, you might also like Episode 94 on Digitized Supply Chain with insights from Arun Kumar Bhaskara-Baba, Head of Global Manufacturing IT at Johnson & Johnson. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us. We would love to share your thoughts with other listeners.

Special Guest: Antonio Hill.

Episode 99: Augmented Lean: The Book

Tulip — Wed, 12 Oct 2022 00:00:00 -0400

Augmented reveals the stories behind the new era of industrial operations, where technology will restore the agility of frontline workers.

In this episode of the podcast, the topic is "Augmented Lean Prelaunch." Our guest is Natan Linder, in conversation with host, Trond Arne Undheim.

In this conversation, we talk about the background of our co-authored book, Augmented Lean, a human-centric framework for managing frontline operations, why we wrote it, what the process has been like, the essence of the Augmented Lean framework, and the main lessons of this book for C-level executives across industry.

If you like this show, subscribe at augmentedpodcast.co. If you like this episode, you might also like Episode 96 on The People Side of Lean with Professor Jeff Liker.

Augmented is a podcast for industry leaders, process engineers, and shop floor operators, hosted by futurist Trond Arne Undheim and presented by Tulip.

Follow the podcast on Twitter or LinkedIn.

Trond's Takeaway:

Industrial revolutions are rarely chronicled as they are happening, but this industrial revolution will be. There is an ongoing shift in the way technology and workforce combine to produce industrial change, and it is happening now. We are lucky to be situated in the middle of it. And I personally feel fortunate that I was brought along for the ride.

It has been a life-changing experience to realize the power and impact of living through a shifting logic of manufacturing and, perhaps more importantly, to realize that as excited as we can be about automation, an augmented workforce represents the best combination of the most important technology we have which is human workers themselves with the second best machines that humans create. The fact that making humans and machines work together is no trivial task has been pointed out before but documenting what happens when it does go well in the biggest industrial companies on the planet feels like a story that deserves to be told.

Transcript:

In this episode of the podcast, the topic is Augmented Lean Prelaunch. Our guest is Natan Linder, in conversation with myself, Trond Arne Undheim.

Augmented is a podcast for industrial leaders, for process engineers, and for shop floor operators hosted by futurist Trond Arne Undheim and presented by Tulip.

Natan, good to have you in the studio. How are you today?

NATAN: I'm great. How are you? It's been a minute.

TROND: It's been a little minute for us. It's crazy with book launches. It takes a little out of you. And you are running a company in addition to that, so you had some other things on your plate too.

NATAN: Yep, running a company and having a book coming is an, I don't know if an artifact, but definitely, company is a lot about changing the status quo. And the book tries to capture a movement. So I think they go along nicely.

TROND: Yeah, Natan. And I wanted to bring us in a little bit and converse about why this book was written. Certainly, that's not my benefit. You brought it up to me. But what were we thinking about when writing this book? So I want to bring it back to way before I came into the picture with the book because it was your idea to write a book. What was on your mind? What were the main reasons that you thought I really want to write a book?

NATAN: When I was coming up as an engineer...and my background, I'm not a pure manufacturing production type engineer, but I've been around it my entire career just because of the type of products that I've been involved with whether it's mobile phones, or robots of all sorts, 3D printers. So you get to spend a lot of time in these operational environments, shop floors, machine shops, and the like.

And when we started working on Tulip, it was pretty clear pretty quickly that there's a moment that is emerging in operations that no one has captured the story. And this is back even; I don't know, maybe five or six years ago. We are maybe one or two years old, and I'm already starting to think about this post-lean, or classical lean movement that I'm sure is happening. That really is the genesis of the book in the early, early days.

And fast forward to when we started talking, I think we got Tulip off the ground. But really, that was a platform to meet all those different people who helped operations transform digitally, whether it's all sorts of consultants, or academics who are researching operations, or business leaders, you know, tons of factory managers and the engineers that work with them, and the executive, so a whole bunch of people. And they're all basically talking about the same thing and the deficiencies in lean, the complexity of technology, and how they're trying to change, and it is so difficult.

So I think that's a good description of the landscape before diving in to try and capture what the book attempts to capture.

TROND: Yeah, Natan, I remember some of our early discussions. And we were dancing around various concepts because clearly, lean is a very broad perspective in industrial manufacturing focused on reducing waste and many other things. It's a broad concept that people put a lot of different things into.

But I remember as you and I were thinking about how to describe this new phenomenon that we do describe in the book, we were thinking a little bit that a lot of these new influences come from the digital sphere. So there's also this term agile. There are some people who say, well, you know, let's just replace lean because it's an outdated paradigm. And I remember you were quite adamantly arguing that that's not the case. And this goes a little bit to the message in our book. We are in no way really saying that lean isn't relevant anymore.

NATAN: On the contrary.

TROND: Tell me a little bit about that.

NATAN: A really simple way I think to frame it is that whether you're practicing lean formally or some variant of it, of lean, or Six Sigma, or some program that formalizes continuous improvement in your operation...and we're talking about frontline operations. We're talking about factories, and labs, and warehouses, and places like that. You are practicing lean because this is how the world..., even if you're not doing it formally; otherwise, you're not competitive. Even if you're in a bank or a hospital, you might be practicing lean.

And that's where agile comes to the picture, and it was adopted widely by operations practice in general and pushed into areas that are not pure manufacturing. So, in a way, lean is a reality. Some organizations are more formal about it, some are less, but definitely, they're doing it.

Here's the issue, and this is the main thesis of the book. When lean came about...and we know the catalyzing text. We know the teaching of Taiichi Ohno. We know about The Goal. We know about The Machine That Changed the World. And those are seminal texts that everybody reads. And we know about Juran and lots of great thinkers who thought about operations as a data-driven game, some from the school of thought of quality, some from pure operation research, some from how do you put emphasis on classic just-in-time, Kanban, Kaizen, all those continuous improvement things.

But at the end of the day, all of that thinking, which still holds true, was not done when digital was top of mind, where data is everywhere, where people need to live in such data ecology. It was done, so to speak, in analog times. And it doesn't mean that the principles are wrong, but it doesn't mean they don't need to get augmented. And this is maybe the first time where this idea of augmentation, which, to me, augmentation is always about...I always think about augmentation from a people's perspective or an org perspective. It's just a collective of people. That's where it starts, and that's where we had something to say. So that's one aspect to think about.

The second big one is actually very simple. It's kind of like; we heard ten years of industry 4.0 is going to change everything, and all we got is this lousy OEE graph. And that's kind of like a little tongue-in-cheek on we were promised flying cars, but we only got 140 characters. I mean, come on, stop talking about industry 4.0. It's like, who cares?

If the tools and digital techniques and what have you is not adopted by the people actually doing the work, that then collectively, one engineer, another engineer, another operator, a team lead, the quality lead, and so on come together to transform their org, if that's not happening, then that's not sustainable transformation, and it's not very relevant. Again, augmentation.

TROND: Right. And I think, Natan, that's where maybe some people are surprised when they get into this book. Because it would be almost tempting to dismiss us as traditionalists in the sense that we are not really going whole hog into describing digital as in and of itself, the core of this principle. So there is a little bit of a critique of agile as an idea that agile or using that as a kind of a description for all digital or digital, right? That digital doesn't change everything.

And I guess I wanted to reflect a little bit on that aspect because I know that you, as a business leader now hiring a lot of people, we are spending a lot of energy bringing these two perspectives together, and it's not very obvious. You can't just take a digital person who is completely digital native and say, "Welcome to the factory; just do what you do. And because you do things better than everyone else, we are now going to adapt these factories." How do you think about that?

In factories, you could conceive it as the IT versus OT, so operational technologists versus information technologists and the various infrastructures that are quite different when those two things come into play.

NATAN: So my frame of reference is the most value...and it's a very engineery frame of reference because I'm an engineer at the end of the day. It's like, the most value gets unleashed when people truly change how they work and adopt a tool, and that's true for operations and manufacturing. But, by the way, it's also true for the greater business perspective.

And a lot of people, when I talk to them about Augmented Lean, really take us to the realms of what is the future of work, and I think it's very timely. We're kind of in a post-COVID reality. Working remote has changed many things, working with data. Big ideas like citizen development, you hear them all over the place. And use of advanced platforms like the no-code/low-code that allow people to create software without being software engineers become a reality. So there's a much broader thing here.

But if I focus for a second on what you're asking, the way I see it is when people truly change how they work, it means that they believe, and that belief translates into action, that the tool that they're using is the best way to do something. And they become dependent and empowered by it at the same time because they're not willing to go back to a state where they're not thinking and working with data, or back to the clipboard, or back to being dependent on an IT department or a service provider to give them some technical solution. People have become more self-sufficient.

And it turns out that if you do that, and sometimes people would refer to that as you let people hack or go nuts in the factory floor or in whatever operational environment, that could be a concern to people, and that's a fair observation for sure. And that's where when you look at the book, when we were kind of constructing the framework we call Leader HG where HG stands for hack and govern... We are used to Silicon Valley startups being like, oh yeah, you all just need to hack. And that's a very glorious thing, and everybody understands that.

And they want them to hack when they are a 50,000-person software company. They're still hacking, but they're doing it in a much more structured way, in a much more measured way. So even in hacking, there's governance. And in operational environment, governance is equally important, if not more, because you're making real things. That is something we've observed very empirically.

Talking to a lot of people seeing what they do, it's like, yeah, we want the best ideas from people. How do we get it? What do we do? We tried this approach, that approach. And I think we were sometimes very lucky to be observers to this phenomena and just captured it.

TROND: Yeah. And I wanted to speak to that a little bit. I want to thank you, actually, for bringing me into this project because you and I met at MIT but from different vantage points. I was working at Startup Exchange working with a bunch of very, very excellent MIT startups in all different domains, and you were an entrepreneur of several companies. But my background is more on the science and technology studies but also a management perspective on this.

But I remember one of the things you said early on to me was, "I want to bring you in on this project, but don't just be one of those that stays at the surface of this and just has like a management perspective and writes future of work perspectives but from like a bird's eye view. Come in here and really learn and go into the trenches."

And I want to thank you for that because you're right about many things. This one you were very right about. And this clearly, for me, became a true research project in that I have spent two years on this project, a lot of them in venues and factory floors, and discussing with people really at the ground level.

And for me, it was really a foundational experience. I've read about many things, but my understanding of manufacturing, frankly, was lacking. And you could have told me as much, but I actually, frankly, didn't realize how little I knew about all of the factors that go into manufacturing. I had completely underestimated the field. What do you say to that?

NATAN: It's interesting because I feel like the last two years, everything I think I know [laughs], then I found out that I don't know enough. It just kind of motivates you to do more work to figure out things because it's such a broad field, and it gets very, very specific.

Just listening to your reflection on the past couple of years, the reality is that there is a gap in the popular understanding of what operations and manufacturing is all about. People think that stuff comes from some amorphous factory or machine that just makes the things. And they usually don't see, you know, we have those saying, like, you don't want to see how the sausage is made, which is obviously very graphic.

But you also don't see how the car is made unless you're a nerd of those things and watch those shows like how things are made, but most people just don't. And they don't appreciate the complexity and what goes into it and how much technology and how much operation process it consumes. And as a society and as a set of collective economies and supply chains, it is so paramount to what's actually happening.

Just take things like sustainability or what happens with our planet. If we don't learn to manufacture things better and more efficiently with less people because we don't have enough people in operations, for example, our economies will start to crumble. And if we don't do it in a way that is not just sustainability from the perspective of saving the planet, also that, but if we don't become more efficient in our supply chains, then businesses will crumble because they can't supply their customers with the product that they need.

And this thing is never-ending because products have life cycles. Factories have life cycles. And the human species, that's what we do; we take technology, and then we turn it into products, and we mass produce it. That's part of how we survive. What we need is we increase awareness to this. And I think The Machine That Changed the World and Toyota Production System unveiled those concepts that you need to eliminate waste to build better organizations, to build a better product, to have happier customers; there's something really fundamental there that did not change.

The only thing that changed is that now we're doing it in a reality where the technology is out there; data is out there. And to wield it is difficult, and there is no escape from putting the people who do the work in the center. And to me, if we are capable of doing that, the impact of this is recharging or rebooting lean in the classic sense for the next three decades. And that's my personal hope for this book and the message we're hoping to bring in. We would love people to join that call and fly that flag.

TROND: Yeah. I wanted to take us now, Natan, to this discussion. A lot of people are saying, "Oh, you got to market manufacturing better, and then people will come to this area because there are interesting things to do there." But more broadly, if we think about our book and why people should read that, my first reflection is building on what I said earlier that I didn't realize not just the complexity of manufacturing but how interesting it was.

My take after two years of studying this is actually that there's no need to market it better because it is so interesting and fundamental for the economy that the marketing job, I think, essentially has already been done. And it's just there's a lag in the system for new employees, new talent. And society overall realizes how fundamentally it is shifting and reconfiguring our society.

But I guess I want to ask you more. What is the reason a C-level executive, whether they work in manufacturing, in some industrial company, or really, if they work in any company that is interested in what technology and manufacturing is doing to their business reality...how they can implement some of those ideas in their business. What would you say to them? I mean, is our book relevant to a business leader in any Fortune 500? Or would you say that our messages are kind of confined to an industrial setting?

NATAN: I think it applies to all of them. And the reason is that these types of roles that you're describing, folks will best be served if they learn from other people's experience. And what we tried to do in the book is to bring almost an unfiltered version of the stories of their peers across various industries, from medical devices, to pharmaceuticals, to classic discrete manufacturing, all sorts of industries. And they're all struggling with the same kind of stuff. And so those stories are meaningful and can contextualize the thinking of what those C-levels are actually trying to cope with.

What they're really trying to do, everybody, I'd say, is why do people think about and talk about those big terms of digital transformation? It's really because they want to make sure their companies don't stay behind or, in other words, stay competitive. This stuff is an imperative for organizations that have real operations that span digital and physical, and I don't know many that don't. Of course, there are some service industries that don't have anything but still have operations.

You can't avoid handling the subject and what it entails. It entails training your people differently. It entails defining technology stacks. It entails connecting using various technologies, protocols, what have you, across organizations and finding value in this data so you can make good decisions on how you run your billing cycles, or how you order your stock to build, or how you ship your end product and everything in between.

And I don't think that the book is groundbreaking in the sense that we're the first people who ever thought about it. But I think if we've done anything, is we've observed long and hard. And we've listened very carefully to what people are telling us that they did, and they struggled. And it's a timely book. And maybe in a decade, it's a classic, and, wow, these are good stories. And it's like reading about the first people booting up mainframes or PCs. And if that happens, I'm actually pretty happy.

But you know why I would be happy? Trond, let me tell you something, it's because technology, like, the human needs change much slower than how technology evolves and gets deployed, but still, good technological-driven transformation take a long time.

TROND: That's exactly what I was going to say is that the future is an interesting concept because what's tomorrow to some people is today for others. So you say we're not writing about something that's so new or unique but to industry overall and to some manufacturers, what we're writing about is the future because they haven't implemented it yet.

To some of Tulip customers, to some of the great companies that we have researched in the book, whether they be J&J, Stanley Black & Decker, DMG MORI, a lot of other companies in medical device side, and also smaller and medium-sized companies, even some startups that are implementing some the Augmented Lean principles, to them, this is of course not the future.

And maybe, you know, we're not saying that leaders who try to implement Augmented Lean need to change everything around; we're saying common sense things. It's just that; clearly, all of industry is not human-centric, right? There are parts of industry where you adjust 80% to your machines, and you make economic decisions purely based on the infrastructure efficiency improvements you're trying to make. I guess what we're saying is the innovation argument; people are the most innovative, and you have to restructure around your workforce, even if you are making machine and robot investments.

NATAN: Yeah, automation would always require strong reasons to automate that, you know, some of them are complexity, safety risk, things like that or throughput to like how much product do you need and that kind of stuff. But even if you have the best automation, you typically have people around it, and nothing is just only machine-driven or only human-driven.

The reality is that most stuff gets made through a combination of several manufacturing technologies working in unison with people at the beginning, middle-end doing things from the planning, to running automation setups and machinery, to taking the output, doing assembly, doing tests, audits and checks, and packaging, and logistics, and at the end of the day, human-intensive type of operation in most of the areas we roam, at least.

And as such, to think that in this day and age you don't focus on people is to me nuts when all those people carry a supercomputer called a smartphone in their hand and have uber-connected homes with a million CPUs streaming all this data, and we call that media, whatever. And they're so accustomed to interfacing to their world and their businesses through that.

And you and I are Gen Xers, and let's just think about the generation that comes after us and after us. These are digital natives par excellence. They expect as much, and organizations that don't do that, whether they choose the Augmented Lean approach or any other approach, they're just not going to have employees. That's a little bit of a problem.

TROND: Yeah. But it's important what you're saying in one respect which is there are many reasons to dismiss a book, a management book, a technology book. And one could be like; all these people are just that. And one, I guess, gut reaction when people look at the title or perhaps hear some of the things that you and I are saying is that, oh, these people are Luddites; they're against technology.

But I wanted to, certainly on my end, just to state very clearly there's nothing in our book that's against technology. We're simply saying to optimize for the simplest technology, that is, you know, to our great inspiration here, who was a big inspiration, I know, for you and now for me because you brought her into my sphere. Pattie Maes' perspective from MIT on Fluid Interfaces and the importance, you know, no matter what advanced technology you're going to bring into whatever context, if that context of the technology, the use interface is not a fluid interface, you are simply doing yourself a disservice.

You could have bought a $1 million CNC machine or maybe a $10 million whatever robot, but it has to work in your own organization, and this is just so important. So we're not against technologies. We're just saying these investments will be made. But you have to think about other things as you're making those investments. So I just wanted to make that point and hear your comment to that.

NATAN: Yeah, look, I have a slightly...I guess a complementary angle to this is like when you think about it; I think that technologically democratized organizations in the day and age we living in the future. And what makes, I think, Augmented Lean span beyond the frontline operation perspective is because it tells a story of democratizing operation where fundamentally before lean...and we're talking about the mass production era. Mass production came from a military structure, you know, divisions, and battalions, and commanders, and ranks, and all that kind of stuff.

Enters lean, and democratization starts. Forget technology. It starts because suddenly everybody on the Gemba Walk, you know, the walk where they have an equal voice to find problems on the shop floor, and list them up, and think about a solution, everybody has a voice. So these are fundamental things that shifted things like how you manage your warehouse, or how you do just-in-time, or how you are supposed to do continuous improvement. But you have to collect data to prove that this improvement is actually worthwhile doing.

And this is exactly what agile took, and this is exactly the transition you saw in, well, because the market moves so fast and the internet is here, and clouds are real, why don't we not spend two years in a bunker doing waterfall software development? And, boom, we're now talking sprints and all that kind of stuff. And no one is even questioning that. And that's a lean approach we call agile, lean approach to how you do software development.

And what I'm trying to say is, de facto, when I run a day in a company, like, I talk to my peers, and my leaders, and folks I work with on a daily basis. Everybody talks, yeah, we're on an operation sprint. We are on a marketing sprint. We are on a whatever sprint. What is that? That is a democratized organization with specific leaders owning functions and owning interfaces using tech stacks all over the place: the marketing stack, the sales stack, the HR stack, whatever.

And where we roam also, we're part of the operational or OT stack, and that's what they're doing. And all this book is doing is saying, like, hey, it's actually happening. Let's give this a name. Let's put the beacon on this. Let's try and find what's the commonalities. Let's get the best stories that share the successes and the failures. We have plenty of failures there in the book that teach you something at this moment in time and set up the next decade.

This next decade to me, is seminal. It's not very different to when technologies reached maturity, like clouds and what have you. 10, 15 years ago, you're talking about this thing, cloud, some people will go like, "What cloud? What are you talking about?" That's done. That's the disappearing edge of technology. Now we say AI and all that kind of stuff. And then the problem gets solved and disappearing, you know, it's like, so that's going to happen. I just think we gave it a good name and a good description at this point in time.

TROND: Natan, I love the...personally, I'm a runner. I love the metaphor of a sprint, and for a couple of reasons, not just because I know what a sprint is and what it takes. But I love the fact that a sprint in a management context refers to sprinting partly together because it's a team-based effort. So some people need to sprint a little faster in certain aspects of that team process in order to deliver things that the team needs.

But rounding up and thinking about how people can sprint with us, Natan, how should people think about learning more? So, obviously, reading the book. It's available on every bookstore, and Wiley published it, and it should be everywhere. There's even an e-book.

But beyond that, what are your thoughts about how people can get in touch, join the movement, join the sprint of thinking about Augmented Lean? Which by the way, there is no one Augmented Lean principle. It's a menu of choices. There are ways that you can engage. There are ways you can implement it. It's not like a one, three-step process that everybody has to do. But there are ways that people can connect. We have this Augmented Podcast. What are your thoughts if people are gelling with this message?

NATAN: I can talk about my heart's desire, okay, and my hallucination around this. And this is like, really, kind of living the dream and making sure democratization continues. If we are successful, at the moment, we are starting a movement. And there are millions of people who self-identify as lean Six Sigma quality professionals out there that know exactly what we're talking about viscerally. They spend their days trying to solve problems like that. They pore over data; they train people. They are the people creating the reports and trying to kind of help their organization take another step and another step in the never-ending journey of continuous improvement.

We need to work on a much larger manifesto for Augmented Lean, and this is not for you and me; this is for a greater community to come together. So my recommendation is if you dig this and this is something you want to do, you know where to find us; go to augmentedlean.com. There's a contact email, our contact information. And I guess we can share it for that purpose somewhere in Augmented Podcast or our various other channels. And tell us what you think. And just join us.

We're not sure exactly...we're starting from the excitement around launching the book with our close network of partners, and friends, and customers, and collaborators, and all our network. And it's a very exciting moment for us. But we're going to open it up, and it's going to be in the book tour, and it's going to be in various conferences.

And the first law of creating a movement is show up. So I'm calling everybody to show up if you're okay with lean and the way it's going so far for you and Six Sigma. But if you feel the need to change and observed or experienced some of the stuff we're talking about in Augmented Lean, come tell us about it, and let's shape it up and get people together. The internet is the best tool on the planet to do that, and we'll get it done. Stay safe.

TROND: Right. So, on that note, I want to round us off. I think that it should at least be clear from this conversation that both of us strongly feel that there are greater things ahead for industry and that manufacturing is not just a relevant piece of society, but there are things happening here that are coalescing that we are describing in the book, but that will happen independently of us and the very few examples we were able to put into the book.

And folks that are interested in exploring what that means for them as individuals, as knowledge workers in the factory floor, or as executives who just want to be inspired the way people were inspired by the Toyota lean movement or other movements, they should come and contact us. Natan, thanks for spending the time today.

NATAN: Yeah. Thanks, Trond. Always a pleasure. Will see you very soon.

TROND: You have now just listened to another episode of the Augmented Podcast with host Trond Arne Undheim.

The topic was Augmented Lean Prelaunch. Our guest was Natan Linder, in conversation with myself, Trond Arne Undheim. In this conversation, we talked about why we wrote a book and why C-level executives should read it.

My takeaway is that industrial revolutions are rarely chronicled as they are happening, but this industrial revolution will be. There is an ongoing shift in the way technology and workforce combine to produce industrial change, and it is happening now. We are lucky to be situated in the middle of it. And I personally feel fortunate that I was brought along for the ride.

If you liked the show, please subscribe at augmentedpodcast.co. And if you liked this episode, you might also like Episode 96 on The People Side of Lean with Professor Jeff Liker, who wrote the best-selling book, The Toyota Way. Hopefully, you'll find something awesome in these or in other episodes, and if so, do let us know by messaging us because we would love to share your thoughts with other listeners.

The Augmented Podcast is created in association with Tulip, the frontline operation platform that connects the people, machines, devices, and systems used in a production and logistics process in a physical location. Tulip is democratizing technology and is empowering those closest to operations to solve problems. You could find Tulip at tulip.co.

Augmented — industrial conversations that matter. See you next time.

Special Guest: Natan Linder.