NEXT POINT ZERO —?Chapter 1: The meaning of Industry 5.0

NOTE TO THE READER: This is a book chapter draft. Feel free to comment and propose ideas to improve and continue it.

From craftmen to robots

The term Industry 4.0 was coined by the German Government in 2011 as part of a new industrial research strategy?[1]. It is inspired by the notation used in software development to indicate new versions of a product that have significant differences from the previous ones. In this sense, Industry 4.0 hints at a fourth major revolution in the industrial sector.

But if we’re talking about a fourth industrial revolution what were the first three about?

Historically, up to around 200 years ago, the manufacturing capability of humankind has been substantially limited to craftmanship: people using manually operated tools to cut, shape, polish, weave and assemble pieces of material.

Then came the first industrial revolution, sparked by the diffusion of the steam engine, the invention of the first mechanical tools and high-volume production processes that revolutionized many industries: from the production of textile, metal, glass, paper and chemicals, to agriculture and transport. Activities that were once carried out in a distributed way within households began to be centralized in factories and saw a dramatic increase in productivity. Many other social effects generated from this shift, e.g. the start of urbanization and radical changes in the labor market, which are however outside the scope of this work. It’s enough to say it wasn’t just a technical matter: it shaped politics, economics, and many other facets of society in a deep and enduring way up to this day?[2].

The first industrial revolution happened in Europe and North America, starting in 1760 and up to 1840, after which, for a few decades, the manufacturing world went on without much disruption. This until the 1870s, when a new wave of innovations started spreading: mass steel production, diffused railroad networks, cross-continental telegraph lines, the first telephones, and electrification, among many others technical advancements in production processes, paved the way for a new phase of globalization and huge additional productivity gains. This second industrial revolution culminated with the rise of assembly lines for the mass-production of cars, first in 1901 at the Olds Motor Vehicle Company, and later in 1913 at the Ford Motor Company for the famous Model T, where some of the first systematic time-and-motion studies were made to improve efficiency, laying the ground for the establishment of the modern industrial engineering practice [3].

Between the first and second world war, a great number of discoveries and technological advancements were made, many of which driven by military investments. However, the overall manufacturing sector didn’t see important changes until the advent of computers, robotics and automation, which allowed some or all phases of production to be carried out without the direct intervention of humans. The first industrial robot was installed in a General Motors facility in 1961 and since then, the growing adoption of automated processes dramatically increased productivity once again and allowed mass production in many industries beyond automotive, disrupting not just the technological process but also business models.

Whether the automation of processes actually represented a revolution is debated. Some define the third industrial revolution as the currently ongoing shift toward a globally distributed, fluid and hyperconnected economy. However, the term Industry 4.0 was coined to represent an ideological jump from the manufacturing standards of 2011, which to the German government seemed distant enough from the early 20th century paradigms to deserve a “number” of their own. For the purposes of this book, we will follow this perspective.

The fourth industrial revolution

So what is this fourth industrial revolution about?

For many the answer is related to a series of cutting edge technologies such as cloud computing, artificial intelligence, virtual or augmented reality, advanced robotics and so on. But there’s much more than hard-tech in this.

Let’s take a step back for a moment and think about the most important forces shaping the industrial sector: customer demand and competition.

A global market started emerging in the 1980s thanks to cheaper transport and more powerful communication means, and became the norm with the spreading of the internet and the ever easier movement of people, goods and capital. Private and business customers gained an ever growing choice of brands and suppliers to choose from, increasing their bargaining power. Plus, businesses from lower income countries could easily offer lower prices thanks to cheaper labor.

In this scenario, for manufacturers in high income countries competing on price only is almost always a failed strategy, as labor costs can be up to ten times higher than the competition in lower income states [4]

Thus, to survive and thrive, businesses in all sectors in the more advanced economies have started to differentiate their offering to focus on less price sensitive customers, investing in product innovation, quality, customization, service level. But, unfortunately, none of these can benefit from traditional economies of scale based on production volume.

This is key. The first three industrial revolutions all had a common thread: an increase in productivity and capacity linked to technologies that allowed economies of scale, or in other words, being able to produce more at a lower cost. But with a modern customer focused on diversity, service, quality and customization, increased productivity through higher production volumes could not be the answer [5].

Businesses thus reacted taking two different approaches, both of which paved the way for this new industrial revolution.

The first one was finding means to increase productivity without increasing volumes: hence, the focus on robotics to reduce labor costs throughout the supply chain, artificial intelligence to predict and prevent machine failures, or to automatically detect defects through machine vision. In R&D, companies started using advanced simulation software (Digital Twin) to anticipate issues in the engineering of complex systems, and additive manufacturing (3D printing) to speed up and reduce the costs of prototyping.

The second approach was to create more value for customers, via servitization [6]?and mass-customization [7]?of products. Again, to provide products as a service in a profitable way, the products must be able to be controlled remotely via IoT technologies. Mass-customization on the other hand requires distributed supply chains and production lines that can share data and adapt in near real-time from anywhere, requiring a location-independent IT infrastructure (Cloud Computing).

In both cases, and even more so after the pandemic struck, an additional emphasis was put into remote monitoring and control systems, which required a two-way connection between the real and digital world, the so-called Cyber-Physical System (CPS).

The adoption of these solutions is not simply the result of technological innovation. It stems from a drive to stay relevant and acquire ever more demanding customers. It started in consumer markets, but with a growing percentage of the world population getting accustomed to new business models and higher levels of service, it has been trickling gradually into the B2B world in all industrial areas.

A systemic upheaval

Beyond the industrial world, the rise of digital products and services has had an enormous impact on our lives.

The huge advances in software and computer hardware, accompanied by the internet and the spread of mobile devices, have allowed innovations in all fields beyond manufacturing: banking and financial services; marketing and advertising; telecommunications; design, media production, gaming and other arts and entertainment fields; publishing; pharma and general scientific research; legal; security and law enforcement. Some of the biggest revolutions are yet to be seen, among which the emerging technologies in mobility and energy, nanomaterials and biotech sectors.

Even if this book is focused on the manufacturing sector, I cannot and do not want to underestimate in any way the impact that such changes had, are having and will have in our world. These trends are part of our daily lives and will be for the foreseeable future.

As a side note, the logistics sector, driven by the rise of e-commerce, is an interesting case study where both digital and industrial technologies joined forces to bring about truly disruptive changes. But still, this could be the subject of many books on its own and is outside of the scope of this one.

The vision for Industry 5.0

The fourth industrial revolution is far from being fully played out yet. So what’s the point of marking a new tick in the scale of industrial revolutions already?

A few years into its application, the 4.0 paradigm had become synonym for a fully automated, almost dehumanized industrial sector. The emblem of this is the idea of the “lights-out factory”, a manufacturing facility that can work without human intervention and thus without lights. It is an idea that was, and probably still is, the north star and holy grail of many strategic industrial initiatives.

However, while lights-out factories may be achievable and desirable in some specific cases, people started to notice that, in general, technology in and of itself was not enough to achieve substantial improvements like it was in the previous industrial revolutions. In line with this view, the Japanese government decided to switch up gears another notch by presenting in 2017 a vision named “Society 5.0”, hinting at a step forward from the industrial trend that Germany had launched six years earlier. The vision aimed at a lofty goal:

?A human-centered society that balances economic advancement with the resolution of social problems by a system that highly integrates cyberspace and physical space.?

— Japan Cabinet Office Website [8]

The key here is?human-centered.?In this sense, Society 5.0 is not a technological advancement from the 4.0 model, as it brings no additional technology and is not a separate revolution. The name served to refocus the use of existing technologies as enablers of a better standard of living for people and society as a whole rather than a simple driver of efficiency and competitiveness in a specific sector.

Following a similar vibe, and in the wake of disruptions brought by the COVID pandemic, the European commission picked up the idea a few years later and published its “Industry 5.0” vision, referring to more resilient, fair and inclusive supply chains that would take advantage of technology not just for their own economic benefit, but to provide sustainable value to all “stakeholders”, that is, all the people.

?Industry 5.0 provides a vison of industry that aims beyond efficiency and productivity as the sole goals, and reinforces the role and the contribution of industry to society. It places the wellbeing of the worker at the centre of the production process and uses?new technologies to provide prosperity beyond jobs and growth while respecting the production?limits of the planet. It complements the existing “Industry 4.0” approach by specifically putting research and innovation at the service of the transition to a?sustainable, human-centric?and?resilient European industry.?

— European Commission Website [9]

Once again the centrality of the human being emerges. Interestingly, the EU commission explains that the 5.0 model?complements?the 4.0 one rather than being a different, more advanced revolution, and rightly so. Once again, they are not different stages in term of scientific and engineering achievement and they cover the same set of technologies. However, like the Japanese Cabinet, the European Commission decided to set a distinct name for this new vision, to take distances from an excessive focus on technology in favor of a more holistic perspective that would also take into account the wider range of stakeholders involved in the manufacturing process.

This is very appropriate since, as you will see later, the vast majority of 4.0 programs can be fully successful only by putting people front and center anyways. The concept of human-centricity in technological innovation initiatives is one of the foundational concepts of this book, one that in fact goes well beyond a specific technological wave. As a matter of fact, it is not a new idea and it has been around at least since the Renaissance, six centuries ago. In our time, the most innovative companies have been practicing this principle for decades. Therefore I will not dwell too much on the difference between 4.0 and 5.0 and just speak about 5.0 from now on.

As you read, you will come to appreciate how people, sustainability, and shared benefit in any innovation initiative are extremely important as a value in and of themselves, but also as a competitive advantage. I hope that by the end of the book this perspective will become the default lens for imagining and realizing your professional future and that of your business.

Implementing the 5.0 model

We’ve seen how Industry 5.0 is becoming the new paradigm to drive value in this emerging competitive landscape and in society as a whole.

Some applications of cutting edge technologies have allowed companies to reduce costs while increasing quality, not unusually with double digit improvements where projects have been carried to completion. This is already a totally viable business case.

But regardless of how enticing these results may seem, looking at technology adoption only for production process efficiency is a limited perspective that brings?relevant financial risks?and leaves much higher returns on investment (ROI) on the table. Industry 5.0 can be in fact much more than just production technology and needs not be a high risk endeavor.

In the scope of transformation programs, I find useful to define Industry 5.0 as a?people-centered, technology-enabled, data-driven approach to value creation, and as such, in its broader application, any process and function can benefit from it, with the potential of pushing overall company performances to a completely new level.

So what’s the gap between improving productivity via some piece of shiny new, IoT-enabled equipment on the shopfloor and the broader value creation approach?

There are two.

1. Risk and Medium-Term ROI

Adopting some of the so called “enabling” technologies* require significant investments of cash and internal effort. Beyond the investment itself, the project success relies on the interaction of a variety of highly specialized skillsets, which, with the exception of large enterprises, most companies do not have in house. For this reason, it’s often hard to even evaluate with accuracy the competence of external partners and the quality of their work until the project is over. On the other hand, acquiring all the necessary knowledge internally may take too much time and the costs could easily overtake the expected returns. That’s why risks are, in many cases, inevitable when learning to do new things. But if the project scope is limited to a single performance or process, it’s easy for the risks to become too big to be taken on.

The value creation approach instead, looks beyond the shine of cutting edge technologies to find the opportunities with the highest return on investment, which may well be improvement that do not require big outflows of cash and can be fully accomplished in a few months—if not a few weeks—using technologies that are cheaper and more consolidated and thus present lower risks (there will be examples of this later in the book). Furthermore, taking a broader perspective helps to reap benefits not just in a single step in the process, but on the entire value stream [9].

2. Culture and Long-Term Advantage

Introducing a new technology with the only business case of improving a single performance will do just that, and nothing more. The process, and in turn the company, will be only marginally better. The competitive advantage gained, if any, will last only until the other players in the market will do the same, and they will. Plus, if you’re playing catch up with those that have already taken steps in this direction, you’re lucky if they will not have improved further by the time you’re done, canceling any ground you thought you gained on them.

On the other hand, the value creation approach will literally transform you and your company by nurturing a data-driven mindset focused on the customer and continuous improvement. These are strategic assets that will allow you to overcome competition and stay on top of it for a long, long time.

This is not to say that your shiny new, IoT-enabled shopfloor equipment is not useful, quite the contrary. But it will reach its full potential only in a context where its productivity is supported by equally innovative processes and people. In other words, technology will make significant impact only if and when it will help people to either?do things differently?or?do different things [11].

1. Website?of the German Federal Ministry of Education and Research website (in german)?
2. Similar shifts in society happened in the following industrial revolutions too, but none, in my opinion, has so far transformed the face of the world and its inhabitants in the same way.?
3. FOCUS: The birth of industrial engineering: Time-and-motion (T&M) study was the combination of Time Study by Frederick Winslow Taylor, and Motion Study by Frank and Lilian Gilbreth. T&M studies were part of the Scientific Management approach, first proposed by Taylor in his book “Principles of Scientific Management” (1911). Taylor’s work became a fundamental reference for management professionals, so much so that nowadays Scientific Management is mostly referred to as Taylorism, and his book was nominated the most influential in 20th century business literature by the Academy of Management in 2001. The Gilbreths also had a huge influence in the field. Through their work and writings, they laid the foundations for Human Factors studies—including ergonomics and industrial/organizational psychology—and for the application of the continuous improvement process. LINK
4. LINK, LINK
5. It is true that more volume is not the answer in the manufacturing sector. But “traditional” economies of scale have still a role although in a different form.
6. The simplest and easiest example of a servitized product is home rental. Other cases include long-term car rentals with maintenance and insurance included, mobility sharing (bike, scooter, car etc.), and the famous Power By The Hour? model implemented by Rolls Royce on its jet engines.
7. The fashion industry is ahead in this game. A good example is the production of custom designed sneakers offered by Nike, but there are many other boutique firms providing personalized clothing and eyeware. The automotive industry adopted just-in-time strategies initially as a means to higher efficiency, but later also as a value driver to provide customers with the opportunity to choose their own set of optionals and colors.
8. Source
9. Source
10. The value Stream: Some of you may be familiar with the term “Value Chain”, which represents the various functions and processes that generate value within a company. The concept of value stream is slightly different, in that, while still considering different functions and processes, it focuses on a specific product or product family sharing the same resources. In this sense a single company may have multiple value streams. The Lean approach stresses the importance of identifying value streams in the business and making sure that value “flows” without obstacles and without generating waste from beginning to end. This perspective is very effective in helping companies reduce costs and become more agile. For more information, we suggest reading “Learning to See”, by Mike Rother and Jim Shook.?
11. The management of a company I worked with was excited about the brand new metal punching machine which had just been installed in the factory. Among other things, it could increase productivity compared to the equipment it replaced by cutting multiple designs on a single metal sheet. The machine worked great, but the planning office and the workers themselves did not know how to exploit this feature and kept using the machine cutting a single design at a time. Getting used to the new machine actually reduced productivity and months later the company was still in the process of catching up.?