Original title: Scale and the levers that provide DAOs their power
By Rowan Yeoman
Translated by: Johnny J, SeeDAO Translation Guild
Goodbye "business model", hello "network economy"
As we described in our recent article “DAOs are not things, they are flows”, Web3 offers a new paradigm that makes it possible to replace the old, company-centric paradigm that has been evolving for 400 years.
If we can move away from this paradigm of viewing companies as centralized entities and stop viewing DAOs as entities and instead view them as decentralized networks that coordinate the flow of resources, we will have a whole new perspective on business and economics.
DAOs and companies are essentially two different systems. Companies are business models, while DAOs are network economies. This fundamental difference is the key to DAOs’ potential to lead a new paradigm.
To understand what network economics are, how they differ from business models, and why they are more powerful, we need to use some conceptual frameworks to explain them. The concept of "scale" is our weapon to understand this; to explain scale, I will focus on Geffrey West's research on the dynamics of system expansion.
We can see a more complete explanation of this dynamic here, however, there are two fundamental dynamics that we need to understand at a high level:
This article will first introduce you to these two dynamics. If my overview is good, then I hope that you can clearly understand that these two systems are the key to stimulating the energy of DAOs.
West’s research began with an understanding that biological systems scale sublinearly. This means that as organisms (mammals, insects, trees, etc.) grow in size, their internal systems become more efficient. For example, if a mouse were to double in size, it would only need 75% more food, oxygen, water, etc., because its heartbeat would slow, and it would live longer. This prediction has been accurate from mice to elephants to blue whales; every doubling of size corresponds to a 25% increase in efficiency. The mechanism that produces this phenomenon has to do with a concept called fractal scaling hierarchies.
Biological systems are fractal layers (sort of like branching structures), where each additional layer increases efficiency. A great example is the mammalian cardiovascular system. All mammals have a heart that pumps blood around our bodies in the same way. The heart pumps blood under pressure into the aorta, which branches into two branching arteries, which then branch into more arteries, and so on and so forth. The system works the same way, the more layers you have, the more efficient it becomes (as you grow, the amount of work your heart has to do to get oxygenated blood to your body's cells decreases). That's why a 220-ton blue whale only needs 11 beats per minute to circulate blood to every cell in its body, while a mouse's heart needs 500 beats per minute to do the same thing. All mammals in between exhibit exactly the same ratio of heart rate to body size.
While this is amazing, what’s even more incredible is that this dynamic system also applies to human-made systems. This scale effect is the fundamental driving force of the company. The essence of corporate development is to establish a set of fractal layers to form economies of scale, which shares the same mathematical laws as the growth of mammals, insects and trees. As the company grows larger and more hierarchical, each level of its structure becomes more efficient, and the production cost per unit of goods decreases with the increase in size. This is called sublinear scaling, that is, as the size of the system grows, the utilization of resources becomes more and more efficient.
Fractal layering is limited
Systems that rely on fractal stratification to bring about scale effects can scale incredibly efficiently. But the downside is that these systems decay and die in tangible ways. The life span of all animals is almost perfectly predicted by their body size (for mammals, life spans range from 1-1.5 years for mice, 60-70 years for elephants, and 80-90 years for blue whales). The bigger you are, the longer you live - but you will die eventually.
This is because fractal (hierarchical) structures are rigid structures. Their strength comes from the underlying structure that can form economies of scale, but over time, this structure will decay and it will have to invest more and more resources to maintain its operation. At the same time, because it cannot change its structural rigidity, it will eventually not survive.
As a side note, humans are the only animal that has bucked this trend and now live about twice as long as we would have based on our body size. And this has only happened in the past few hundred years, thanks to breakthroughs in medicine, hygiene, nutrition, etc. Until the 19th century, our average lifespan was between 20 and 40 years, which was commensurate with our body size.
Companies are masters of fractal structures
It is this dynamic that has underpinned the company’s 400-year success. The creation of the limited liability company gave us an efficient system to operate this dynamic—allocating capital, building infrastructure, and scaling business models…over and over again.
However, similar to fractal layers in biology, companies are finite. They continue to expand their business models, but over time they can no longer grow. The underlying structure requires more and more resources to maintain, and eventually dies.
This extinction is often not obvious, and companies will do whatever they can to stay alive. For example, they may engage in anti-competitive behavior—acquiring or merging with other companies that are still growing, or they themselves may be acquired by another company (even if the company is essentially dead, it will still keep the brand). But a widely circulated analysis shows that even with all these strategies to avoid extinction, almost all companies eventually decline and die in a visible way.
Another powerful force West points to is social networks, and the social output they bring in a superlinear fashion. When we refer to social networks here, we mean pure networks of human interaction, such as friend circles, business relationships, religious communities, membership clubs, etc. - any collection of social relationships.
The superlinear scaling of social networks is based on a set of predictable network dynamics, including Metcalfe's law.
This is how mechanisms like markets work. The more participants there are in a market network, the greater the likelihood that valuable exchanges of goods and services (trading as social outcomes) will occur, and the greater the value of the network.
This means that as a social network grows in size, its social output grows at an increasing rate. Studies have shown that if a social network doubles in size, its social output will more than double: 115% more, to be exact.
This dynamic applies to all types of social output, but we are interested in the generation of creativity and innovation. The conclusion of the West team is clear: the expansion of social network size will lead to superlinear growth of creativity and innovation. This is a direct result of the exchange of ideas, knowledge, capital and creative collaboration on a larger scale.
The problem for corporations is that once they mature, it is almost impossible for them to successfully leverage this social network-driven dynamic. They must work on building scalable hierarchical structures in order to capture the benefits of economies of scale, which means they tend to develop a highly rigid infrastructure that makes real innovation almost impossible. Although they will try to innovate, innovation is not what the corporation as an organizational form is good at.
Some companies do do R&D to drive product line extensions etc but this rarely leads to real innovation and most companies are reduced to buying innovations produced by others from the outside rather than innovating themselves. As hierarchies become more entrenched and rigid they do this more and more in an attempt to stay right and prevent their inevitable decline.
But cities won’t die.
This is where West’s analysis gets really interesting. While animals, plants, and companies are known to die predictably, there are few examples of cities dying throughout history.
It turns out that cities have survived (and thrived) because they have been able to harness both of these dynamics — sublinear hierarchical expansion and superlinear social network-driven innovation.
Cities use extended layers to build roads, power grids, water supplies, hospitals, emergency services, communications networks, schools, etc. This means that the larger the city, the more efficiently all of this infrastructure can be built, resulting in more amenities and a better standard of living.
On the other hand, as cities grow, they also have larger and larger social networks, which leads to more creativity and innovation (and all the other social outputs). If a city doubles in size, it produces 115% more research papers, patents, startups, etc.
This dynamic system brings a virtuous cycle of innovation and improvement to the city. The city's innovative ability creates a steady stream of new businesses, replacing those that have died and bringing in new funds; income is increased, infrastructure is invested in and improved, and the city is renewed. This in turn brings about another virtuous cycle - the improvement of the lifestyle and future expectations of urban residents attracts new residents, thereby improving the efficiency of dynamic one related to infrastructure construction, and at the same time improving the efficiency of dynamic two related to creative innovation.
What about DAOs?
You probably already know where this is going. DAOs, as network economies, have the potential to leverage both dynamics 1 and 2. After all, cities aren’t things… they’re networks!
Fundamentally, companies are about building fractal-scaling organizations, and everything they do is centered around that. Steve Blank, a professor of entrepreneurship at Stanford and Berkeley, distinguishes startups from mature companies in this way:
In this framework, we can see that startups operate like a social network — a group of founders who are well connected and highly creative and innovative as they trial, error, iterate, and pivot in the hope of discovering a repeatable, scalable business model.
Then, once they find a repeatable and scalable business model, they commit to building and solidifying the infrastructure to scale that business model. They position their strategy and business units to implement that architecture. After that, it’s hard to change.
DAOs are network economies that don’t pursue a business model like companies do. As network economies, DAOs are more like cities, free from the rigidity and limitations of companies. Also because of the properties of network economies, DAOs can take advantage of both of these dynamics; they can be engines of new experimentation and discovery, led by communities of individuals aligned around a common goal. They can also scale these innovations to benefit the world.
This is possible because network economies can coordinate in more complex and efficient ways than corporations can. A DAO network can contain multiple subnetworks. Rather than a single centrally controlled entity, it contains many autonomous self-organizing groups - all working towards its overall goal in a more flexible organizational structure; some groups build to expand the layer, others work to explore and create.
Like cities, DAO networks benefit from the same positive feedback loops as they grow, thanks to drivers 1 and 2. Growing economies of scale make them powerful, while continued creativity, innovation, and responsiveness keep them alive and connected to a changing world. Because of this, they attract more and more talented people who are looking for opportunities to do valuable things, who in turn support and grow the DAO network.
This is what web3 promises us! This is what DAOs promise us! It’s a network of inspired individuals that can collectively fight against our entrenched economic system, trillion dollar incumbents, and 400 years of inertia.
To do this, the DAO must be able to leverage both motivation one and motivation two.