How concepts emerge

We can better understand how innovations will evolve if we stop looking almost exclusively at the core technology and instead appreciate the hidden power of the concepts around that technology play. Indeed, the greatest innovations are really new concepts, not technology. Mankind’s first transformative innovation, agriculture, came about not because people learned to use a scratch plow attached to an ox. Once people started farming, they could produce more food than they needed. Only once we could do that, did we have time to paint (art was now possible) or study nature (science was born). It allowed for larger societies that required us to establish governments, laws, and armies. Much of what we now consider society came about because of the scratch plow and the ox.

But the scratch plow was not fundamentally a new technological innovation. The first versions were simply sticks of a certain shape that could be used to dig lines in the ground, making it easier to plant large amounts of seeds. Before the concept of agriculture emerged, people might have used that stick as firewood. Now they used it for something else.

Burial chamber of Sennedjem, Scene: Plowing farmer.
We call this shift—from firewood to scratch plow—the “conceptual shift:” The conceptual shift that people make that informs them how to use a technology.
As we will argue later, there are a number of new technologies that make it possible to coordinate human (and non-human) activity in new, decentralized models. The issue that is limiting the adoption of such technologies, and the realization of their potential, is not an understanding of those core technologies but rather an adoption of a concept, or set of concepts, that tell us how to apply those technologies, in the specific case considered in this White Paper, to the coordinating of human and machine activity inside a firm.

When you begin to observe the shifting concepts around technology, when you understand the pattern by which they evolve, you can better understand how innovations will evolve.

Sometimes these shifts take long times to evolve. Salesforce was founded in 1995 introducing a new way to deliver software. But it was not until their concept was given a name decades later—“cloud computing”—that enabled people to understand their software that cloud computing really took off. It was not until people could comprehend what Graham Bell called the “telephone” that engineers, corporations, and users would “get” what this technology really was for.

To understand the potential implications of any new concept, like RenDanHeYi1 which we believe could be as transformative as what Alexander Graham Bell’s “Telephone” (as concept not only a technology) was to communication or “Cloud Computing” has been to software when Salesforce.com introduced it, we must dissect how the conceptual shifts new technology are changing.

Luckily, there is a lot known about how concepts emerge. In social sciences a theory of social movements explains how movements such as the American Revolution, the Polish Constitutional movement of 1791, the British abolitionist movement, or the Russian Revolution of 1905 came to be. In science, Thomas Kuhn wrote a breakthrough paper that broke down how “scientific revolutions” come to be—how did we shift from believing the sun went around the earth to putting the sun at the center of our system—resulting, ultimately, in a paradigm shift. Mathematicians studying how new terms (e.g., the sine function, the zero numeral) and theories come into being lay out a convincing four-step process.

All of these approaches to understand how concepts emerge share remarkable similarities. Here we mash them together to lay out a simple framework of concept emergence. It explains, we think, why Blockchain right now is so hard to comprehend, and what it will take for society to embrace the true potential of the Blockchain concept.


1. discontent with current concepts

The process through which a concept emerges likely begins with the perception that current concepts are inadequate (e.g., to explain anomalies or to solve certain problems). They may be responding to perceived anomalies or failures of the existing concepts2 or reveal inadequacies by addressing previously unrecognized practices3 4. Both studies of mathematical concept emergence and of theory evolution speak to an individual or group noticing that observable phenomena are not adequately addressed by existing theories or models. Social movement theory contends that an informal group is more likely to become accepted as a field if it seeks to solve a problem that existing fields cannot adequately address.

2. introduction of new concepts

New words, naming new concepts, are introduced. In theory evolution, researchers introduce new “constructs” that will form the building block of a new theory. In mathematical concept emergence, mathematicians may introduce new “intellectual technologies” (Schoenfeld, 1994) or “language tools” (Rorty, 1989) that facilitate solving the problem. These new words, and the concepts they name, begin to define the community behind the new concept, theory, or potential field, as, per social movement theory, the informal community begins distinguishing itself.


3. the formation of a field

The concept and, potentially, the theory or field created through the use of the concept are tested and adjusted. In theory evolution, a new or revised theory is proposed and then tested for its predictive value. In mathematical concept emergence, the formal system, once manipulations have been performed, is translated into the real world for testing. In both cases, where the new or revised concept/theory adequately improves prediction or does not adequately fit observation, adjustments are made. Per social movement theory, we can reasonably assume that this testing and adjustment are taking place during the steps in which the informal community shares papers and attempts to engage other communities in dialogue. 

4. Rejection, incorporation, or replacement

The new concept/theory interacts with existing concepts/theories and is rejected by, is incorporated into, or replaces existing concepts/theories. While mathematical concept emergence and theory evolution address the social aspects of the process with less emphasis than social movement theory, all three suggest that the new concept/theory will ultimately fit existing, accepted concepts/theories. This fit can be achieved when the new concept/theory (a) supports and does not challenge existing concepts/theories or (b) successfully replaces existing concepts/theories. The new concept/theory, failing to fit or replace existing, accepted concepts/theories, may alternatively be rejected. 


We believe that in the specific case of the emergence of a new, alternative organizational concept, we are at the breakout point somewhere between phase 2 and 3. In other words, several alternatives have been introduced and experimented on. Most have proven inadequate. But now, clarity is forming around a new organizational concept.

New organizational concepts

Firms have been experimenting with alternatives to bureaucracy. Over the last two decades, several such experiments have gathered interest (phase 2 of concept emergence). These include the team of teams, open organization, Holocracy, and blockchain/ DAOs.

Team of teams

In the military, General Stanley McChrystal found that by reorganizing the tight, hierarchical structure of the Joint Special Operations Task Force into a “team of teams,” they became more effective at fighting agile, asymmetrical enemies. Despite the military’s advantages of size, equipment, and training they were ineffective against Al Qaeda in Iraq. Al-Qaeda in Iraq was unlike anything traditional military principles had prepared him for. Composed of decentralized units, they would appear to attack and then melt into the population. Without a formal reporting hierarchy, they offered no clear power center to target.

He experimented with a new organizational philosophy he called a “team of teams.” He broke his organization down into small independent teams then overlaid an “umbrella” team—a team of teams—to help units coordinate with each other. His military force started winning.

Open Organization

Red Hat, the leading open-source software company, realized that its long history of organizing communities of independent developers to collaboratively develop software could also apply to how it organizes itself. They began adopting a model they call the “Open Organization,” which has no top-down hierarchy but is composed of people with a common purpose. Decision-making is inclusive and the CEO, rather than dictating, is tasked with convening conversations and encouraging debates.


Companies like Zappos are experimenting with a new organizing concept called “Holocracy,” which CEO Tony Hsieh describes as “turning everyone into a mini-CEO.” Instead of employees having permanent roles and titles, they sign up to perform the jobs that need to be done to help the organization succeed at that moment. Their roles may change week to week. These roles are broken into smaller pieces than full-time jobs, so at any given time you may have as many as twenty roles.


The success of companies Uber and AirBNB have led numerous companies to explore the idea that instead of producing, owning, and selling things, they might instead facilitate providers and users of things to find each other. Microsoft’s recent resurgence is driven in part by its adoption of this philosophy. Its LinkedIn business helps professionals find each other and find employers, Skype helps users communicate, and its XBox-only gaming platform helps game developers reach a massive community of gamers.


Blockchain started as an alternative to traditional currencies, showing a currency can remain viable even without a central bank to control it. But the approach is now making its way into numerous new applications—education, digital rights management, supply chains. Wherever a central authority exists today a blockchain-like model might allow communities to regulate themselves instead.

From experimentation toward clarity

Many of these experiments are being conducted in walled-off parts of organizations, isolating them from traditional approaches in what Mike Tushman (and co-authors) coined as the “ambidextrous organization.”5 This has been critical because some of the characteristics of these structures are incompatible with traditional bureaucracy and cannot, or at least have difficulty, coexisting with or interacting with a bureaucratic model.

Many of these models have proven problematic and seem unlikely to reach sufficient “escape velocity” of adoption to make it into phase 3, let alone 4, of concept adoption. Each of these models enjoyed periods in which they were broadly discussed, but most have eventually confronted complications.

The Holocracy movement, for example, grew popular as Zappos and a handful of other aspirational companies began adopting it. This model introduces several interesting elements that help organizations coordinate human effort through non-hierarchical means. For example, instead of assigning permanent roles, employees pick tasks that need to be done over the period (e.g., over the week) and assemble their own job for the week. In this way, Holocracy replaces the centralized job assignment function to a marketplace. However, this internal marketplace of work is not a true marketplace because one central work assigning body is meant to decide what jobs need to be done. Employees are essentially operating in a one-sided marketplace with all employees on one end and one centralized job provider on the other.

But our research shows that an alternative to models may be finally coming into focus, composed of five clear organizational approaches, most of which do not enhance, but instead replace the traditional hierarchy.

These elements are core elements of the RenDanHeYi model which was introduced by Chinese appliance giant, Haier. This organizational philosophy and system composed of several innovative characteristics including the breaking of large hierarchical units into “Microenterprises” (MEs), turning support functions into profit centers that must sell into the enterprise rather than cost centers, and relating to employees as intrapreneurs. As assessing the Haier model is the primary focus of this White Paper, and much is already written about this model, we will not add great detail of the full model or its history here.


  1. The term RenDanHeYi, roughly pronounced “RenDanHyoy,” is a composite of three Chinese terms: “Ren” refers to the employees; “Dan” refers to the user value; and “HeYi” means combining the two, resulting in the combing meaning of “the value to the employee is aligned with the value to the user.”
  2. Kuhn, T.S. (1962). The structure of scientific revolutions. Chicago Uni. Chicago Press.
  3. Fleck, L. (1979): Genesis and Development of a Scientific Fact. Chicago and London: University of Chicago Press.
  4. Rorty, Richard. Contingency, irony, and solidarity. Cambridge: Cambridge University Press, 1989.
  5. See https://hbr.org/2004/04/the-ambidextrous-organization