Making words for Industry 4.0: How we talk about where we're going

The Foo-Cow-Wee indigenous American tribe lived along the banks of a river in my hometown. Now lost to history, they were a source of wonder and mystery. We'd take visitors to search the shifting banks of the river looking for arrowheads until we were seemingly lost. Looking at our hot and bewildered guests eventually we'd yell into the sky:

"Where the Foo-Cow-Wee?";-)

So too, what is our search for Industry 4.0 if not a search for the right words, a look back into a moving history? How do we arrive at the definition of an "era" especially a new one that is just taking shape?

With the same small town spirit in mind, I ask you to indulge yourself in a longer-post, a meander along the riverbanks of history, to find perhaps a moment or two of delight and discovery.

Industrial Eras 1.0 to 4.0: Middle Ages to the Present

With the goal of situating the Fourth Industrial Era in a historical context, the following is a brief history of economic eras. This history is prefaced with an acknowledgment of the complexity of describing entire “eras” of human history using ...words.

“Words, words, word. Once, I had the gift. I could make love out of words as a potter makes cups of clay. ...I could cause a riot in a nunnery.” ― Jeffrey Eugenides, The Virgin Suicides 

The reason for touching on semantic nuances is the open nature of the factors informing the language of the "era" of the Fourth Industrial Revolution (“Industry 4.0”). In contrast to the closed system predictability of previous eras, many aspects of the Industry 4.0 era are fundamentally emergent and unpredictable. Therefore, the language for discussions of this near-future era is relatively improvisational.

Yeah, we got ourselves some fine Eye Oh Tee, want some?

Hartwell (p. viii. 2017) notes “Any term used to represent a complex historical process runs a "semantic hazard" when it becomes common currency.” De Geus (1997) underscores the semantic hazard of terms used for new eras.

For example, in contrast to previous eras, defined by characteristics of control, hierarchy, and equilibrium, the characteristics of Industry 4.0 suggest the opposite: indeterminant, “open,” disruptive, and transformative (van Tulder, 2019, p. 1). Further, Industry 4.0 characteristics emphasize organizational decentralization (Bartlett and Ghoshal, 1998) complexity, exponential growth, speed, unpredictability, and change (van Tulder, 2019).

Sometimes it is better just to ...

As punctuation to this definitional indeterminacy, the Internet of Things (IoT), a key Industry 4.0 technology “has not yet been consistently defined in academic literature” (Oberlander, 2018). A review of the literature between 2010-2018 identified 16 different definitions of IoT (2018). And this improvisation around terms also applies to artificial intelligence, machine learning and the many other new-tech cousins showing up at Industry 4.0 family gatherings.

As de Geus (1997) cautions, labels for an economic era are helpful, but until we develop a “new language” much of the “real meaning” of a new era, like Industry 4.0, is “not yet digested.”

The historical definitions of eras described here are based on changing economic factors, with an emphasis on the role of technology. In this review, “critical production factors” (CPFs), such as labor, resources, or capital, or knowledge, serve as guides for a perspective on economic eras.

As de Geus (1997) notes, terms like the “Capitalist Era” “New Economy” Information Age” and “Knowledge Society” are derived by distinguishing the dominant CPF of the period in question (de Geus, 1997, p. 199). Further, and importantly, the use of CPFs to label economic eras is informed by the dual aspects “material and social,” Marx uses to describe humans as producers (Callinicos, 2011).

Critical production factors of eras

Starting 1,000 years ago, de Geus notes (1997) in a “primitive Western world” the CPFs were “land and natural resources” used for “producing goods to sustain the population” (198). The long ascent of the “Capitalist Era” occurred between the 1500s and 1960s, when “capital” as CPF produced “goods and services” in excess of “immediate needs for consumption” (de Geus, 1997). Moreover, during this era, technology increasingly drove a faster speed and greater impact of CPF adjustments. 

Behold! Laissez-faire economics

For example, due to technological advancements, in the late 1700s, the CPFs of land and resources were increasingly overtaken by access to labor as the CPF (Fogel, et al., 2015).

This was due to Adam Smith’s advancement of laissez-faire economic policy, which increased access to capital, especially in the 16th and 17th centuries. In turn, improved capital flows allowed for the purchase of early mechanization technologies, such as the steam engine and the mechanical loom.

In turn, this early shift from craft production to mass machine-based production, or industrialization, required increased labor. It was this convergence of several “causal forces” alongside others, rather than “one force” which explains a “turning point and also a take-off” for the First Industrial Revolution (Hartwell, 2017 p. 59).

 Technologies that optimized economic operations, like bigger merchant ships and more capable machines, increasingly meant the capital needed to create mass production technologies had a higher value than the resources being exploited, or the labor (aka "humans"), operating the technologies (Braudel, 1992, p. 365).

The expansion of capital continued into the late 1800’s ushering in the Second Industrial Revolution (Landes, 1969) of interchangeable parts, the standardized assembly line of Henry Ford, and increasing uses of electrical energy in economic life.

Economic processes and organizational models, during this era increasingly attached to “machine-like” efficiency models attuned to running on an infrastructure based on steel, oil, and railroads. Large-scale factory management principles were “rational, calculable, and controllable” (de Geus, 1997, p. 19) employing the principles of Fordism and Taylorism.

Increased productivity and infrastructure, resulted in lowered prices for goods creating social and “economic disturbances” (p. 114, Wells, 1890), but also overall significantly improved living standards in industrialized countries.

For example, by 1890, a deficient harvest in any one of the countries of Europe” no longer resulted in “starvation” as wheat was accessible by railroad and steamships connected to the “combined production and consumption of the world” (Wells, 1890, p. 334). Noted Wells “the days of famines for the people of all such countries have passed forever.” (Wells, 1890, p. 335).

However, by 1914, and the cataclysm of World War I, “the dangers of the Second Industrial Revolution” revealed that

“the power to bring unlimited prosperity could also bring unlimited misery.” (Mokyr. J, 1998, p. 147).

Moreover, while the Second Industrial Revolution ended in 1914, the Capitalist Era continued its deep global “integration” of financial markets, goods, and technologies (Bordo, M.D., 1999) as well as penetration of sociopolitical structures (Harvey, 2007, p. 10) in the decades that followed.

Fueled by increasing access to global capital and markets, early stirrings of the Third Industrial Revolution were underway by the 1960s.

Circuit boards are groovy

A shift from mechanical to digital manufacturing, automation, computers, and electronics gained momentum as the “Digital Revolution” by the 1980s. By the 1990s, this “new convergence of communication and energy” was creating a powerful new infrastructure (Rifkin, 2011, p. 2). 

Use of computer technology, based on integrated circuit boards, microprocessors, alongside the invention of the World Wide Web in 1989 (Tim Berners-Lee) began driving one of the “most exciting social, cultural, and political transformation in history” (Cohen, 2013).

The traditional, hierarchical, and “centralized” organizational, economic, political, and business practices of the First and Second Industrial Revolutions will, according to Rifkin, (2011), be “subsumed” by the open and distributed business practices of the Third Industrial Revolution (Rifkin, 2011).

In fact, Rifkin argues (2011) that easy capital credit and debt, as well as cheap oil and resulting climate change (Klein, 2015), are leftover facets of the Second Industrial Revolution, and finally tipping into an “endgame” (Rifkin, 2011, p. 15,). 

Capitalism is dead: Long live Capitalism!

Further, by the late 1980s, according to de Geus (1997) “capital is no longer scarce,” and he declared “The Capitalist Era had finished!” (1997).

Notably, others argued that indeed, the Capitalist Era was not what it once was, but that via “increasing geographic mobility of capital” (Harvey, 2007, p. 92) and other sociopolitical factors, capitalism had morphed into a “neoliberal ideology.”

In either case, the notion that knowledge had “displaced capital as the scare production factor - the key to commercial success” (de Geus, 1997) has taken root. Specifically, the CPF of the era has shifted to knowledge workers, (de Geus, 1997; Drucker, 1999) described as, “those who have access to knowledge and know-how to use it” (de Geus, 1997, p 199).

Moreover, this was “useful knowledge” is defined (Kuznets, 1971) as the source of modern economic growth (Mokyr, 2002, p. 2) with an emphasis on the centrality of technology (Drucker, 1999; Kuznets, 1971; Mokyr, 2002).

In general terms, most people are engaged with the socio-technological factors of the “Knowledge Economy” and the Third Industrial Revolution, with worldwide Internet use in the billions, and mobile-phone subscribers over 6 billion (Cohen, 2013).

Knowledge and technology are engaged in a feedback loop of “exponential growth” (Cohen, 2013) powered by Moore’s Law, the heuristic telling us processor chips double in speed every eighteen months. As a result, the power of the “devices” delivering the ubiquitous “digital” flavor of modern life is also growing exponentially.

Era Sandwich: The juice of previous Industrial eras flavors the present

The “Knowledge Economy” arose within the Third Industrial Revolution, which is ongoing and expanding. Notably, the key to the transformative power of the Knowledge Economy is the “unprecedented speed” (Cohen, 2013) at which it is creating new technologies, like the IoT, as well as a new economic age, Industry 4.0.

In fact, Industry 4.0 is distinguished from previous eras, by “how fast it is penetrating the infrastructure of businesses and governments” (Hyzy, 2016).

Industry 4.0 and The Internet of Things (IoT)

As an emerging era, the perspectives on and definitions of Industry 4.0, remain in flux (van Tulder, 2019, p. 1). Sinclair’s (2017) perspective emphasizes an evolution towards ecosystems of connected processes, “outcome-based” business models, defined as an “Outcome Economy.”

A McKinsey report orients Industry 4.0 around “cyber-physical systems” and the integration of “economically disruptive” computation, networking and physical technologies and processes (Manyika, 2013).

Industry 4.0 “embodies blurred boundaries,” argue Gotz and Jankowska (van Tulder, 2019, p. 385), in all aspects of a “connected enterprise” in an “ecosystem of humans, machines, and organizations.”

Therefore, “collaborative clusters” based on mutual trust, norms, and values, notes (Gotz, 2017) are “the answer” to Industry 4.0 requirements and challenges. 

Rifkin (2015) does not use the term Industry 4.0, instead emphasizing a paradigm shift from market capitalism to a “collaborative commons.”

In his preface, Hartwell (p. viii. 2017) reminds “Any term used to represent a complex historical process runs a semantic hazard when it becomes common currency.” However, further, hedging on the Industry 4.0 definition as settled is not simply for semantic reasons - it is core to issues at play.

In contrast to traditional eras, with characteristics oriented around clear definitions of control, hierarchy, and equilibrium, several of the key characteristics of Industry 4.0 reflect characteristics with

indeterminant “open” definitions, which are disruptive and transformative (van Tulder, 2019, p. 1).

These characteristics include organizational decentralization (Bartlett and Ghoshal, 1998) complexity, exponential growth, speed, unpredictability, and change (van Tulder, 2019).

The importance of how organizations and leaders will navigate the changing river of transformations delivered by these “just over the near horizon technologies,” (Moussavian,2018) such as AI, the IoT, robotics, and big data, is vitally important.

Importantly, it involves attention to the history of how we - the lost Foo-Cow-Wee tribe - got here, the words we use, and the language we create to transform the present into the future.