Ken: Good day, and welcome to episode 195 of our Momenta Digital Thread podcast series. Today, we're pleased to host Luke Smaul, our newest Strategy Partner at Momenta. Luke has worked in the digital industry for over 20 years, applying strategic thinking to new go-to-market and business models. He has successfully spearheaded large multinational digital transformation projects for Fortune 100 companies before bringing his expertise to others. Luke's passionate about creating new business models across various verticals, in both the discrete and process space using IoT Edge sensors, big data, and advanced analytics. He advises global and early-stage firms focusing on digital strategy, sales and marketing, and go-to-market, planning and leveraging his prior experience at GE Digital Flashpoint and his firm Chakra. Luke, welcome to our Digital Thread podcast.
Luke: Ken, amazing to be here. Thanks for having me.
Ken: Well, very happy to have you. I should say, dually, so glad to have you in Momenta and happy to have you on this podcast.
Ken: It's a double pleasure. You no doubt have listened to some of our podcasts before. We call this the Digital Thread podcast, so the key question to start this off is, what would you consider your digital thread? In other words, the one or more thematic threads that define your digital industry journey?
Luke: When I look back at my career, the common thread I see is how you extract value from technology in the industrial space. What I mean by that- is if you go back to the start of my career, I started programming PLCs and grew up with the traditional industrial automation stack, so I went from programming PLCs to connecting PLCs to SCADA systems to programming SCADA systems to connect them to historians. From historians to MES, from MES to ERP. As I was growing through technology, I also grew my career. I found myself in the position around 2015 or 2016 while running professional services sales for North America's industrial automation group at GE. When Jeff Immelt was CEO of GE at the time, his vision for what digital meant for GE became clear, and he established the GE Digital Business Unit. Overnight, my world blew up.
My business unit at the time was rolled into GE Digital. As I said, overnight, my world blew up. All the technology, tools, and techniques I'd use for my career to deliver value to manufacturing customers changed. It was very much industrial IoT or what GE called Predix, Predix, or bust. I had to go back to the first principles and figure out what this new technology meant to manufacture companies. I looked after all our industrial automation projects in North America. I had customer responsibility for all those projects. I had to spend time down in San Ramon, at GE’s new Digital Headquarters, and come up with a hypothesis. What net new value can we gain from industrial IoT in the industrial space? I devised a hypothesis and made enough noise about that internally that they put me in front of Jeff Immelt several times when he was still running GE. I got to present my vision for what industrial IoT meant to manufacturing. Those meetings went well enough that Jeff sponsored me on a team to start going after net new logos in the manufacturing space for GE's Predix platform. With Jeff's help, sponsorship, and relationships, before the sales cycle, we landed Intel as one of the first net new logos for Predix. I got to execute and run that account for about three years. These are the years that everyone has read about in the media around GE Digital's challenges and the challenges around Predix- made Intel successful to a point where we launched a joint go-to-market where we went after the semiconductor supply chain with Intel's help and GE's technology.
I tell that story because the lessons I learned set me on a path to management consulting, having my consulting firm, and eventually joining Momenta. But the reason I tell that story- technology can change. We can introduce net new technology into manufacturing in the industrial space, but how you think about value and how you think about looking after people and outcomes doesn't change. You can make the technology work for you and work for your customers. If you can stay focused on that, and that's been my common thread for my career- it is staying focused on customer value and value in industrial space.
Ken: It's a great story and establishes a platform for your credibility. You've been truly full stack in terms of the technology work you've done, but also that outcome focus which GE was probably one of the first to put the focus on outcomes, even though that had always been how you value in the end. It's interesting because as much as people like to badmouth GE or did at the time because GE had its issues and everything else. Every one of the industrial companies we've worked for still talks about GE Digital as the benchmark. Well, what did they do? They were the early leader in that and everybody else, by definition, is a fast follower. I'm curious because you spent a lot of time there. What are the top three insights you gleaned from this time relative to the digital industry?
Luke: It's such a good question. It was a challenging but highly enjoyable time in my career, and you're right. A lot of people have had their opinions on GE. But fundamentally, corporate innovation is rock-hard. Corporate innovation- what we now often call digital transformation at a scale of GE is rock hard. But some of the things that I saw done well- so, the one thing that they got right was setting a NorthStar early on. This is critical for any digital transformation program. If you're going to go after digital transformation in a big way, you've got to set a very clear branded message around what you're going to go and achieve. There was no question, no matter where you worked in GE, what division, what group, or where in GE Digital you sat, you knew that it was Predix, and that was the focus for GE at the time. That was a considerable achievement for Immelt and his team to get that ingrained into the culture- a culture that was 100 years old, ingrained into everyone in the company was laser-focused on Predix. One is to set your NorthStar.
Second- we did this in some places well, and in others, we were challenged to do this. But once you've got your NorthStar, you've then got to break your strategy into small consumable parts. Start small and focus on product market fit. When you have product market fit, scale with your customers and the market. There was an initiative internally at GE called FastWorks where we took a lot of lean and agile thinking and applied it to an industrial setting. That program, I feel, was highly successful. This idea of starting small, being agile, iterating, learning as you go- very, very far into a product company like GE- what was adopted, especially inside of GE Digital, and highly successful. Then the last was it's all about people. This was around 2016 to 2019 when I ran Intel as an account and made them successful on Predix. This was the same timeframe the articles were written about- the Wall Street Journal has its opinion. Jeff has his own opinion on it. Lots of stuff out there about it, but there was no doubt it was challenging. Because of the people, we got through those challenges with a new platform, market, and outcomes. It was because of the relationships we maintained between Intel and GE, the friendships that were formed, and because people have trusted us to deliver the outcomes we promised from day one. If you've got to do this and do it big, you've got to start with the people.
Ken: There are great learnings in there. It's interesting; I think the CDO, Tanja from Bosch, also mentioned setting the NorthStar. This is one of the first things she's stepped into Bosch doing. I liked the idea of consumable parts. I always think of it as 'think global, act local, grow organically.' How do you build up those components? You started to reflect that this is a change management exercise, not a technology exercise. This is about transformation. Technology is the catalyst, as it often does, which means it's a people exercise right from the beginning. We sometimes lose that when we talk about digital this and digital that. Great learnings. I know you founded your advisory firm, Chakra, in 2019. Great name, by the way. Focused on helping manufacturing companies create, I quote, "A new way of thinking about digital and digital transformation." Tell us a little bit about some of your key learnings and accomplishments during this time. I could say downscaling what you learned from GE more individually.
Luke: It was a great time. We had grown Intel in the semiconductor go-to-market to a point where it was a capstone in my corporate career. I decided to take the lessons from seeing the good, the bad, and the ugly of digital transformation and apply those to our customers and clients. My co-founder and I launched Chakra. Very early on, we were fortunate enough to land one of the giant European OEMs, one of the largest European OEMs. They wanted our help to navigate through what they were doing, which I would classify as digital transformation with a capital T. They tried to move one of their multi-billion-dollar divisions from selling equipment today to selling equipment as a service tomorrow. We partnered with them out of the gate after launching Chakra. The process or the approach we agreed with them was to take 25 people outside of their day jobs, outside of the organization that used to work for this large OEM- have them come, report to myself and my co-founder and run like a startup inside the corporate environment.
We ran that for about two and a half years, successfully built a roadmap from selling equipment to selling equipment as a service, got them through the initial stages of that roadmap, and gained some success. The famous quote from the VP that was responsible for the program on the OEM side was that we went from a concept in the boardroom to a PIO and orders flowing for this new business model in a year, which, if you've done any corporate innovation or big digital transformation, you know a year is a concise space of time. The learnings we've talked about from GE, applied to this mode of working, accelerated us to outcomes in a way they've never seen before. Fun times. Like I said, I got to run that for about two and a half years and got some early traction about a year into it with this large OEM. Some of the big learnings- and it was interesting, like you said, to go from a huge 100-billion-dollar corporation to a two-person company and then try and drive digital transformation at scale. What did we learn? One of the big things we've talked about is people. But it's more than that. It's also who are the people you're going to engage with. We found that digital information, with a capital T, happens in the market with your customers. It doesn't happen in PowerPoint, it doesn't happen in reports, and it doesn't always happen in workshops. You've got to get in markets, you got to spend time with customers, and you've got to learn what digital transformation means to them, and that's what you've got to capitalize on from your internal perspective. You've got to get people out of their comfort zone. This was something, again, that NorthStar helped with GE. We applied the same thinking when we took this OEM to market and drove their digital transformation- taking people out of their day jobs, out of their comfort zone, and running them like a startup.
Imagine a new startup with all the functions available; that's what we built. It was staffed with people from the corporate environment now working in entirely new ways. That proved very successful because they weren't limited by how the organization had always run. Then again, we started small. We launched with a new business model, using SCADA data shipped over email to a central data science team where we could use that data to predict remaining useful life, and that's what we took to market. It was minimal and scrappy, but we focused on the go-to-market or product market fit and go-to-market. It's getting customers on board, and we started to scale up. That was the big learning from that.
Ken: It's interesting. You said to do this in a year was quite an accomplishment. Recall that COVID-19 is the way we refer to COVID. You were doing this against progressively greater lockdowns, remote working- everything else that went. Given that backdrop, I'd say super spectacular in terms of what you accomplished. Remember the uncertainty during that time. None of us were sure what to expect or what this would be. It sounds like you did quite a bit. I appreciate your LinkedIn bio because it was some excellent talking material. I'm going to come back to quoting again. You said, "Manufacturing companies start by investing in digital, but lose their way as they work toward identifying ROI and impact and pursuing scalable solutions." Then you add, "Digital offerings are not geared toward the needs of industrial companies and are not equipped to provide guidance on how these companies do and should operate." You say Chakra is going to solve this. Can you say more about this perspective, particularly around these industries?
Luke: For sure. What I'm referring to there when I wrote that, which is about 2019, was what I classify as the first wave of digital transformation for industrial companies. That first wave kicked off around 2015 or 2016 when industrial companies suddenly started waking up to the high valuations driven by platform-based technology companies. Many big industrials lost their top spots in valuation to these new platform businesses. They were looking at some of these technology companies. The likes at the time of Uber or Airbnb, and a lot of very asset-intensive manufacturing companies or industrial companies. We're looking at these new technology companies, these new platform companies that didn't own the assets they used or didn't own the assets they serviced and were able to drive sky-high valuations. That scared a lot of industrial companies, and they set out on a road of that first wave of digital transformation and what they did- I think this is where some of the mistakes were made along the way, was trying to emulate what they saw coming out of the valley, coming out of these platform-based companies, coming out of these IT companies. The two secret ingredients I'm referring to in that bio that we're missing is deep domain expertise. You can't play in the industrial space, in the manufacturing space, without real deep domain expertise.
I think you saw many companies make mistakes by hiring executives out of IT roles out of IT companies and putting them into industrial companies without that domain expertise, which didn't work. Likewise, from an IT versus an operational technology or OT perspective, the technology itself needed the proper manufacturing and industrial context and needed to be hardened for the industrial space. That was lacking with the first wave of digital transformation. The good news- when I wrote that, it was around 2019. I think in the last three years- COVID has, I think, accelerated this a little bit; we're now seeing what I call a second wave of digital transformation, specific to industrials where we're seeing- you're noticing CDOs are now being placed who's got deep domain expertise, for example. You're seeing technology that's been around since the first wave. Still, it's coming into primetime now that it has that real operational technology or OT focus. It's got the domain expertise baked in, and its industry hardened. I'm pretty optimistic that in the last three years, we can now start to capitalize on the second wave of digital transformation.
Ken: That's a unique perspective. I think you're one of the first I've ever heard refer to it in waves and talk about it as being in the second wave. We probably should have a level set up front because I've noted that we're so loose in how we use the terms digitization, digitalization, and digital transformation. Help me understand how you view these three phases loosely applied to the impact of digital and industry and how you define and differentiate them. What is the difference between them?
Luke: Great question. It's fundamentally why I founded my firm in 2019- the confusion in the market and the confusion with clients and customers around, specifically, digitization and digital transformation. For example, let's take a CNC machine or a machine on the shop floor in a manufacturing plant. Digitization is sensorizing that equipment for the first time. Maybe you can't tell exactly what's happening on a piece of kit, perhaps you can't count the production cycle that's going through, so you put on a sensor, you connect that sensor to an IoT gateway, or you connect it to a SCADA system if you're old school. You can now visualize what's happening on that piece of equipment. That's digitization, at first, the sensorization of a piece of equipment.
Digitalization, you start to make sense of these new sensors, this new data, in the context of the broader production situation. The process itself, digitalization, is meant to be focused on the process. Maybe that sensor that was counting, for argument's sake, parts going through your machine, connect that to an OEE system. You can tell how effective your equipment is in the context of the overall production schedule and process you're running. That's digitalization. It's relatively new that we've refined the difference between digitization and digitalization. I used to confuse those two terms, but I think about digitization as connecting something; digitalization is making sense of it in the context of a process. Where things get interesting is when you separate those two from digital transformation. Digital transformation for me has to be digital transformation with a capital T, where you're driving net new value that was not achievable before, leveraging digital technology. Ideally, that value you're achieving is on the revenue creation side of your business. If you look at the history of digital transformation, I was talking about the valuations earlier. Why many industrial companies are on this journey, you have to think about the revenue side of your business. You have to be thinking about net new value, and you've got to evolve your business to go after that. That may mean you've sensorized a piece of equipment, connected it to an industrial IoT gateway, and pumped some data to the Cloud. You're making sense of that data from an efficiency and predictive maintenance perspective. That's your digitalization-to-digitalization journey, your digital transformation journey. It's what we did with that large European OEM I mentioned; you leverage that data to transform your business model. Maybe you stop selling that piece of equipment in the future, and you start selling machining as a service, and that's where that significant capital T transformation comes in.
Ken: The difference for me- and I appreciate how succinct you were regarding those definition differences- is that you could say digitalization is evolutionary. As you say, the transformation element is revolutionary thinking as a service business model relative to traditional Capex and OEM providers. That is transformational because it redefines how you do business, report revenue, and everything in the company. Yet, digital still is the catalyst for it. I appreciate the difference there, and I think we mix it up too much, demeaning what transformation means and probably going too tech-heavy on why digital is important to even efficiencies that are in there.
Luke: It's so true. Yeah, and we built a maturity model at Chakra, showing the path from digitalization to digital transformation. We very intentionally drew a chasm right after digitalization. A lot of clients I talked to were in what we call the 'digital chasm,' this idea that you were sold on the promise of digital transformation, but what you got was digitalization. You're lacking in the level of ROI that you're expecting, and you're in this no man's land, this digital chasm. We've spent a lot of time in my previous role helping clients crawl out of that and get back to either- maybe realistic expectations on what digitalization could do to your business or reframe the execution side and focus on the big transformative outcomes.
Ken: I like that idea. The digital chasm, of course, is reminiscent of 'crossing the chasm' relative to general innovation. What are some best-in-class manufacturing companies applying digital in their operations and products?
Luke: I've been reading about two recently, so if we split that in half between operations and products. From an operations perspective, a company I've worked with over the years and have always stayed close to is PepsiCo. I think they're doing a lot of things right in terms of their digital journey, in terms of digitalization- to a point where in a recent earnings call, their CEO called out in response to the supply chain challenges we're all living with, the inflationary challenges we're all living with, the general economic headwinds we're all dealing with. He called out their digitalization journey as one of the saving graces to fight against some of those headwinds. They're doing a lot of things right, and I would keep a close eye on what they're doing from a digital perspective. On the product side, one of the companies I've always followed and have a lot of respect for in terms of their digital journey has been John Deere. Did you see that they recently won two CES awards and two Consumer Electronics awards for their autonomous tractor initiatives? I think it's impressive if you're going to be an industrial company. You will play in robotics, connected products, smart product space, and autonomous space. You're competing against some of these consumer players, and you can beat them out and win these awards, which is super impressive. What I like about John Deere and its strategy is they also think about service, so it's not just connected assets for the sake of it. They also offer an enhanced service portfolio based on having these autonomous, connected assets.
Ken: A background in Syngenta, of course, so ag tech. One of the earliest conversations I remember with John Deere at the time was- and mind you, this is probably 12 years ago- that they saw the tractor as a mobile data hub, which is what they called it at the time. Collecting all of the agriculture information, but also serving as a point to make decisions like when to apply pesticides or plant a seed or some form of prescriptive analytics- again, 12 years ago, they deserved it. Also, as a former Coke guy, I can appreciate Pepsi, especially some of its enlightened leadership, how much they've taken on a lot of this because they're multi-category. Not just beverages but snacks and direct store delivery. The granularity of what they do and the number of times they do it daily allows them to improve gradually but show big results over time. Two great examples there. I'm curious, though. How do you know when an organization can adopt digital manufacturing techniques? What practices have you seen in realizing that potential value? Before you answer, another way to think about this is, would you ever walk away from a potential customer coming to you and saying, "We want to apply digital?" What are the criteria you're looking for?
Luke: It's funny you asked. I was talking recently to somebody about this, and it's- would you have said no to that large, giant European OEM when we landed them early on at Chakra?" I was so passionate about the difference between digitalization and digital transformation. If they were just focused on digitalization, would you have said no? A two-person company headed into COVID probably wouldn't have said no. Touché. Yeah, but there were some customers that we've worked with over the years, and we felt like they were probably too focused on- especially digitalization inside the four walls of the plant, that was not the world we were playing in. But from a readiness perspective, I always approached companies and strategy from a digital readiness perspective under four headings. We had a term for that: the 4 Ds at Chakra. The 4 Ds were demand, domain expertise, data, and data science. Demand; two sides to the demand equation. Is there internal demand for it? Do you have C-suite sponsorship to do something interesting from a digital perspective? Likewise, are there customers interested? You don't have to have a product-market fit yet or anything like it, but is there a customer that will sponsor you, co-create with you, and help you get into the market, partner together, and figure out what's going on? That's the demand; you've got to have some demand, domain expertise.
I've touched on this earlier; you've got to have the right domain experts on the team. During that first wave of digital transformation, there was a real lack of domain expertise, so it's something that I always look for in terms of readiness from a client perspective. Data. Again, I touched on this earlier. You don't need big data to transform your company; you can do it with legacy data, with small data with some- I've seen process engineers who've taught themselves Python and MATLAB and are using SCADA data to drive meaningful outcomes. But you got to have some data to start with. But don't delay until you've got a huge data architecture. Likewise, data science. Data science is not a degree or qualification. You don't need to spend a million dollars in salary to hire a Stanford Ph.D. You need to find the right people, like the process engineer I mentioned who taught themselves MATLAB or Python. You have to find the right mindset inside your organization to think about how you leverage data to solve problems. Suppose you can find those four ingredients inside an organization, or you can piece them together with the help of an organization. In that case, you're in great shape to start your digital transformation.
Ken: I liked the way you've broken that up. Demand, domain expertise, data, and data science. Let me ask you to put your prognosticator hat on for a minute. Where do you see the greatest opportunity areas? Let me call this generally Industry 4.0, or often, we're referring to it as Industry 5.0 in terms of that digital transformation of manufacturing as we know it. Where do you see the greatest opportunities there in the next five years?
Luke: I got back and forth on these terms. The tongue-in-cheek I always use is that only engineers would try and define a revolution before it has happened. But all that said, they are important terms, and there are important differences between 4.0 and 5.0. But not to get into a discussion about that. As a general school of thought, the big areas where I see the greatest opportunity around these 4.0 and 5.0 initiatives are three areas. One is data. As you said, we're a full stack, which we call either 95 or S95 stack- PLCs, SCADA systems, historians, MES, etc. How we move data and think about data context through those layers has become quite traditional. I think I look at data companies, I'm thinking about HighByte as a good example- that are challenging our paradigm and letting you insert yourself wherever you need to in the traditional industrial automation stack, extract data, provide context and make sense of that data and move from a very linear way of thinking about moving data inside the four walls of a plant or a connected asset strategy and move it to a much less linear model, a more circular way of thinking.
That's going to prove highly valuable in the next five years. I'm excited about that. The key ingredient, the big change from 4.0 to 5.0, is that people are the focus. That may have been a miss of that first wave of digital transformation that I mentioned, which is akin to Industry 4.0. We've got to focus on the people. This stuff happens thanks to people because of relationships, friendships you can make, partnerships you can make, and ecosystems you can build, and that's all people-focused. That's going to be a huge benefit of focusing on 5.0, and then the last piece- a passion of mine, is the circular economy. I love the circular economy because it aligns with what I think about digital transformation with a capital T and 5.0 as we shift from 4.0 to 5.0. We focus on people, new business models, and new ways of interacting and exchanging value. It will enable things like the circular economy that requires us to change how we think about asset ownership in an industrial supply chain sense. That will be interesting for the future of 4.0 and, more importantly, this shift to 5.0.
Ken: That is well said, especially the one about the circular economy. The very definition of ownership under the Uberization of all industry, if you want to think about it that way, has been brought up by several of our speakers over time and coming out of the World Economic Forum, if I remember right, several years ago, co-authored by McKinsey, put together kind of what is that whole future of industrial? The circular economy is a key part of that and is often not talked about enough unless there's an ESG angle, making it a bit of a popular buzzword. But ownership is what is key to that. As-a-service, if you will, moving from products to as-a-service in time. Bringing it home a little bit, we're very proud to have you as part of Momenta, so thank you for joining us. Can you talk about your remit and focus at Momenta?
Luke: It's so good to join the team; I'm excited to get going. The two big focus areas will be digital transformation with a capital T and value for manufacturers. What do I mean by that? Digital Transformation with a capital T- my specialization for the last four or five years has been moving companies to these large-scale digital transformations from a business model perspective. What do you think about servitization? How do you think about- even something as simple as rather than selling a predictive maintenance app after you've been able to do something like predict the remaining useful life on a piece of machinery? Rather than sell the app as an industrial company, which is rock hard to do, you might use that app's intelligence to offer an enhanced service contract. In that way of thinking, the servitization of outcomes of businesses will be one focus area. Another focus area- and this is back to my digital thread, if I think back to my career, most of the time I've spent has been figuring out what technology means inside manufacturing inside industrial companies from a value perspective. If you've got a smart connected asset play, if you're trying to get into a market, if you're trying to penetrate manufacturing companies with a new connected product, the help I'd be able to provide is making sense of that technology from a manufacturer's perspective and then having to go to market strategy that aligns to that.
Ken: As I said, again, it's very exciting to have you as part of the team, especially our advisory team. These are all core areas, and they undergird many of our venture capital activities. I am looking forward to greater things coming here very soon. In closing, I always like to ask about your inspiration. Where do you find your inspiration?
Luke: I always try and keep fiction and non-fiction books on the go. My current non-fiction book is "The Titanium Economy," written by a couple of practitioners out of McKinsey. They have found a list of manufacturing companies in the US that have outperformed the big tech stocks over the last ten years. They do a deep dive into what makes these companies unique, so I highly recommend "The Titanium Economy" as reading material. In terms of general activity and how I keep up to speed with everything on the market, I spend a ton of time on LinkedIn, so I'm pretty active in putting posts out there. But more importantly, I'm active in the community, so I try and comment on people's posts, share articles, post ideas, and get feedback. If anyone's looking to get in touch or see what I'm up to, LinkedIn is a great place to find me. From a people perspective, I follow a lot of great thought leaders. That phrase is always a struggle- thought leaders on LinkedIn. Someone I highly recommend everybody follow just for his unique and quite skeptical perspective on technology, and especially technology in our space, is Rick Bilotta. Rick keeps me extremely honest in my posts and can call BS if I post anything hyperbolic.
Ken: I will second your thought on Rick Bilotta. He is one of the few I consider to be a thought leader. People lose thought leadership the minute they put on their subtitle, and LinkedIn thought later. Rick's very fact-based, and as you say, he doesn't believe the BS many times out there, so he's got a unique ability to carve through that relatively quickly. Kudos on that recommendation, and I will have to read "The Titanium Economy." That sounds great. It sounds like the modern manufacturing equivalent of "Good to Great" in terms of that. Luke, thank you for sharing this time and insights with us today.
Luke: Appreciate the time. This has been great. Thanks, Ken.
Ken: This has been Luke Smaul, our newest Strategy Partner at Momenta, but obviously, a long-term practitioner of full stack like the ISA95. It's been a long time since I've heard that. Thank you for listening, and please join us for the next episode of our Digital Thread podcast series. Thank you, and have a great day. You've been listening to the Momenta Digital Thread podcast series. We hope you've enjoyed the discussion, and as always, we welcome your comments and suggestions. Please check our website at momenta.one for archived versions of podcasts, as well as resources to help with your digital industry journey. Thank you for listening.
Connect with Luke Smaul
What inspires me?
I spend most of my time on LinkedIn interacting with other industry leaders, making new connections, and learning from what others have posted. Regarding my general interests, you could say I have futuristic tastes. I always have both fiction and nonfiction books in the works, and the topics are usually forward-thinking. I recently read two excellent nonfiction books:
Asutosh Padh's The Titanium Economy: How Industrial Technology Can Create a Better, Faster, Stronger America provides a very optimistic outlook on the future of manufacturing in the United States.
Kevin Roose's Futureproof: 9 Rules for Humans in the Age of Automation offers a fresh perspective on what it means to be human in the future world of AI.