Capitalism is a social technology that directs resources toward valuable uses, increasing the total wealth in society. As a social technology, it organizes people and resources into systems and processes. When capitalism directs resources toward processes that discover valuable knowledge, it becomes revolutionary.
There are many sub-technologies associated with capitalism. Double-entry bookkeeping, joint stock corporations, fractional reserve banking, compound interest, legal contracts, and so forth are all technological sub-systems integrated into modern capitalism. The modern model generally fulfills the function of directing capital toward value, but that doesn’t mean it couldn’t do better. If capitalism is an engine, and if we could open its hood, then where might we find room for improvement?
Today’s capitalism is broken. It’s a financialized economy. That means that money is made more through having lots of it already, rather than from finding good uses of it. This dynamic is why companies stopped investing in employees and switched to cost cuts and stock buybacks. In terms of discovery, only high-risk, high-reward ventures can possibly be attractive to capital purely on the basis of profitability. In this system, there are many good uses for money which are unable to signal their attractiveness.
This situation is the result of fiat money, something that came about after market stagnation in the late 1960s. Even then, the large firm research and development (R&D) model of capitalism was failing to consistently find good uses for money. One area of capitalism worth improving is its sensitivity to value, particularly how it searches for valuable knowledge and then rewards it.
In any market structure, there are two sides of the equation: supply and demand. Each has a particular structure, which isn’t inevitable, and their intersection defines how day-to-day life works for different socio-economic groups. The supply or production side of the market tells a compelling story about knowledge and discovery. The products companies choose to make, the bids they place for resources, and the partnerships they make in supply chains all define how production is structured. How companies process knowledge determines this structure.
Capitalism is typically viewed as a machine for creating value. It does more than just create; its revolutionary strength lies with its ability to discover valuable knowledge. Its productive functions include search, create, and capture. The strength of capitalism as a technological system lies in proportion to its ability to process valuable knowledge, both in facilitating discovery, and in realizing value.
Terence Kealy, author of The Economic Laws of Scientific Research, traces the relationship between scientific discovery and value creation. He juxtaposes two models of discovery. In one, associated with Francis Bacon, called pure or academic science, economic value is disregarded. Science is pursued for its own sake—often funded by government—and perhaps technology might result which then might create value. In the other model, associated with Adam Smith, the incentives to create value lead to technological development. By integrating with the natural technological development resulting from the market, science can both learn and contribute, in a self-funding process. Kealy compares the first model to the communist world order, along with the stagnant centralized empires of the Bronze Age. He compares the second model to the modern industrialized world, with parallels to the vibrant and dynamic Hellenistic Age.
Kealy’s observations present a brutally simple model relating scientific research and value creation. All research requires funding. If conducted, it will lead to some amount of new knowledge, some of which will be economically valuable and some of which won’t. If the value created exceeds the costs of research, then research can continue. Otherwise, it cannot.
The simplicity of the economic model of research begins to complicate when viewed with a higher resolution. In theory, any research will be funded if the minute, marginal benefit derived from a result exceeds the marginal cost of whatever portion of research was needed to obtain it. This means that an economic system of research can discover all possible valuable knowledge so long as its funding mechanism is sensitive enough to minute value signals to properly distribute funding. The structure of the economic system will determine how successful it is at discovering value.
Both pure academic research and industrial R&D follow a similar approach to discovery, which might be called narrow-to-wide. Research delves deep into a particular focus, and value is realized only when a major discovery is made, however, these discoveries are typically very lucrative. Industrial R&D follows this model specifically because of the need to find competitive advantage in a monopolistically competitive market. The only way to gain exclusive knowledge is to devote substantial funding to a private project. Industrial Organization textbooks use advanced math to describe this phenomenon. The logic behind it is easy to grasp.
In a market environment where innovation is present and the sector is controlled by a monopolist, there is always a threat that a new entrant could disrupt the monopoly’s position by imitating its technology. The monopolist, who controls prices, already has little to gain from further innovation. In contrast, the entrant has nothing to lose if they possess knowledge which permits market entry. The monopolist’s love of high prices and freedom from competitive pressure gives entrants a tremendous advantage so long as they have the basic technological ability to compete. This puts pressure on the monopolist to innovate even though they don’t want to.
This condition is sometimes lauded by free market advocates as an example of why capitalism always promotes innovation. It’s not that simple.
The dilemma for the innovating monopolist is that innovation will cannibalize their existing product line by making it obsolete. A trade-off emerges where the monopoly will not want to innovate too much, but if they allow new market entrants by not innovating enough, market competition will lower prices. The trade-off resolves as an equilibrium where the monopoly innovates just enough to prevent widescale entry into the market by many new players, but by deliberately keeping prices high and slowing the pace of innovation, there is some room for a few other firms. Thus, the destabilizing and disruptive aspect of technological innovation resolves as hybrid oligopolistic, monopolistically competitive markets. Typically, these markets segment into product categories where one firm or another has the advantage (ex: business vs home PC users).
The problem with this structure of capitalism is that firms are not seeking to maximize value discovery. They are simply grappling with the market forces which force them to innovate. There are two distinct flaws to this approach. First, a lot of value is left undiscovered. Second, the low hanging fruit of big technological motherlodes diminishes over time. Big, valuable discoveries become harder to come by. The economic system ceases to be as sensitive to value discovery as basic technology matures.
One reason why the U.S. economy stagnated in the 60s and 70s could be due to the loss of sensitivity by this model of discovery. There was no more low-hanging fruit. Meanwhile, former easy markets like Japan were blowing back with quality, competitive technological products of their own. Big fat research projects were failing to secure a competitive advantage enough to justify costs. It seems like the engine of capitalism was stalling out. Rather than fixing the problem, the fiat dollar was introduced.
After the 70s, firm specific R&D declined. Now, easy money and the venture capitalist model are capitalism’s source of discovery. This model is extremely high-risk, high-reward, externalizing the massive costs of failed bets to society. It was a doubling down on the problem and we may be nearing the end of the road with this model. It’s high time to go back and simply fix our engine.
In contrast to the narrow-to-wide approach, there is the wide-to-narrow approach. Kealy discusses how rival coal mines in Britain combined forces to create and improve upon a shared rail line, leading to major discoveries in railroad technology and even in the scientific discipline of thermodynamics. Consider this concept from the point of view of research costs.
Employees for a firm all must learn their job skill and improve it over time. Skilled employees invent new ways to do their jobs better, and any well-managed business will improve its efficiency too. This is called the learning curve, and it’s a natural part of doing good business. Improving skills directly corresponds to realized value in the product, really it’s a form of natural research. When you combine the skills and knowledge of thousands of experienced employees, as the coal mines did, you end up with a tremendous pool of valuable research results at minimal cost.
In this model, every employee ends up with small pieces of knowledge, but which they obtained at an even smaller cost. The process of research has already occurred over the course of doing business. The economic system needs to find a way to pool this knowledge and realize value from it.
Some companies have approached research in this manner. 3M and its invention of the Post-It note is a famous example of this, thanks to the epiphany of a regular employee who came up with the idea while taking notes in his Bible at church. However, if the economic system is going to consistently fund minute research by a wide field of employees, where the results must be consolidated to realize profits, then a formal process is required.
Cooperative game theory describes the concepts behind such a process. The total value realized from pooling knowledge must be recorded and calculated. A system for distributing that value back to participants in proportion to their contribution, and also the dynamic market power they possess, would also be required. If the system is unfair or unstable, the scheme of cooperation would fail. Some technological basis, perhaps blockchain contracts, is needed to create the level of agility required to handle many frequent, small negotiations.
If capitalism can move past the need for high-risk, high-reward innovation, it could restore its revolutionary ability to create value. Even small inventions by small market participants need a way to pool into profitable outcomes. Large corporations need a way to share knowledge and experience to multiply value, rather than walling off experience for competitive advantage. Nevertheless, cooperation without space for competition is little more than central planning. Only with agile technological tools built taking the premises of cooperative and competitive game theory into mind, can the competitive environment find space to share knowledge and turbocharge the engine of capitalism.
In summary, capitalism’s engine draws power from knowledge. It is hindered by the economic logic of narrow-to-wide research. With some improvements, this engine can accommodate the wide-to-narrow model more easily. This would go a long way toward overcoming the stagnant market seen today.
