Complex Adaptive Systems: The Daoism Of Western Science.

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Western science, like all of our institutions, thrives on novelty. New theories and new sciences abound: quantum physics, computer science, network science, string theory. The lines of inquiry are always extending beyond yesterday’s boundaries.

One recently developed science is complexity and complex systems. In a reversal of the traditional reductionism in science – which looks for explanations at ever smaller micro-scales, from molecules, to atoms, and now to hadrons and quarks – complex adaptive systems theory looks at the world holistically as systems, including systems embedded in systems embedded in systems, and asks how they perform at the system level. The economy is a system, society is a system, a firm is a system, a city is a system, a brain is a system, and so on. A system can be contrasted with a collection of objects that are disconnected, like a bag of marbles or nails.

There’s a particular focus on Complex Adaptive Systems (CAS): a class of systems found in many fields such as economics, biology, and social sciences, characterized by a collection of individual agents acting independently and constantly reacting to what the other independent agents are doing. These agents interact locally with each other at the micro level in unpredictable ways, and through these interactions, system-level structures and patterns emerge without central control. 

The concept of emergence is key: unpredictable outcomes occur, without any traceable cause-and-effect links. The scientists’ favorite word in this context is non-linear. Their treasured linear equations are of no use in predicting future outcomes in a complex adaptive system. That means, for example, that the policies politicians and bureaucrats prescribe to fix what they perceive as economic and social problems are useless when viewed through the lens of efficacy, and damaging when viewed through the lens of the independent agents – people – interacting within the system. Their freedom of interaction, the essence of the system, becomes impeded by policy.

Complex Adaptive Systems open up another cause-and-effect problem in business. How can we celebrate the great achievement of hero CEO’s if outcomes emerge, rather than tracing back causally to the decisions and actions of the great business leader?

How do we deal philosophically with the idea that outcomes emerge, without any traceable cause? That’s anathema to Western science. Perhaps Eastern philosophy offers a better approach. In Daoism, the Dao is The Way. The focus is not so much on the outcome, more on the way or the path. There is no outcome, only constant change. The images of Daoism include water and river imagery: the river flows over boulders and pebbles, between mountains and banks, bends left and right, and becomes bigger and bigger, and never stops. Heraclitus famously said that a person never steps in the same river twice, because each time, the person has changed and the river has changed. Change is the essence of existence. The way is universal, we follow it – go with the flow.

Complex adaptive systems that constantly adapt to the changing environment and to the interactions of independent agents are said to be self-organizing. They follow The Way, as the way emerges. They exhibit dynamic change, never stepping into the same river twice. The appropriate observation point is holism rather than reductionism – interconnected Eastern thinking rather than analytic Western thinking.

The pursuit of the Dao – the Way – entails harmonizing with this process rather than controlling it. Embracing harmony is key for adjusting our philosophy. Thus, in CAS parlance, the trade-offs between different levels and agents within a system would need to be inclusive rather than controlling, for the classical concept of harmony is one in which diverse interests prevail in a dynamic balance. Harmony is understood as the ‘unity of any nonidentical objects’, which in their diversity allow for ‘the possibility of new things arising’. Translated into CAS, harmony is inclusive of discord but not overtaken by it. If discord does overtake the system, dynamic harmony loses its integrative quality and breaks up into chaos; alternatively, when it is stifled by uniformity, harmony ceases to exist.

Seen through the lens of business, CAS and The Dao require changes in standard business thinking. Control and prediction have been the twin pursuits of business management. But harmony results from balance, not control. Pursuing innovation in a linear fashion through R&D investment in projects can exclude “the possibility of new things arising” in an emergent way, because it uses reason and analytics to favor some investments and excludes others. Emergence is not even contemplated.

Western science and business management tend to prefer the identification of causal change – or that which we can attempt to control and seek to predict. The new science of complexity is less mechanistic than the standard model, and closer to Daoist intuitive thought. Complex Adaptive Systems, in its nonlinear treatment of change, provides a bridge between East and West, an integrative perspective.

Business Is Not A Set Of Practices Or Strategic Methods Or Planning Techniques. It’s A Mindset

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In the current business era, there’s a lot that seems mandatory: using quantitative methods of strategy and planning, following documented IT-enabled processes, organizing fixed structures that can be captured in org charts, and complying with government-mandated rules and regulations. Even the acts of creativity that contribute to innovation are specified, documented, and captured in software. There’s a bias towards fixed cause-and-effect thinking: if a business takes action X, it will result in outcome Y. We are told that case studies will reveal this cause-and-effect linkage in hindsight, to be re-applied in future planning.

There appears to be no room for individualism, spontaneity, unpredictable interactions, or rebellion. Those concepts are insufficiently objective for today’s business executives, consultants, professors and executives. The goal in business is primarily stability: to make a plan and achieve it, to set targets and hit them, to predict quarterly earnings with accuracy, to define processes in the knowledge that they will be followed unfailingly. The goal is to turn business into a science, with hard numbers, laws, and data-driven methods.

But in excess, this objective approach does not support the primary goal of business, which is value. 

The purpose of all firms is to generate value for customers and value is not objective or measurable or amenable to design or planning. Value is a feeling – a feeling of well-being or satisfaction experienced by customers. Different customers experience more value or less value than each other even when using the same product. Value occurs when the customer has used the product or service and compare the consumption experience with their going-in expectations. Value is subjective from beginning to end – from the search for potentially satisfying experiences to the realization in use to the evaluation after use. 

In fact, it is not the firm’s job to create value. It’s the customer’s role to find the most effective solution to their wants and needs. They can express some doubt or uncertainty that there’s anything available to them that exactly meets their need, although they might buy something that the best available option, even though their satisfaction is incomplete. They’re always looking for the discovery of something better. This is the role of the customer – the genius role of insisting on something better, thereby stimulating innovative action among producers to respond with new value propositions. Together, the producer and the customer imagine a new future value via a new or improved service or product; the producer can help the process along with product enhancements and advertising and PR and perhaps prototypes to help the customer’s imagination along.

If the customer’s imagination is piqued, the firm must commit resources to assemble the product capacity that will put an actual, purchasable offering into the marketplace for consumption. There’s no guarantee that this will be profitable or successful. The customer has the final decision. There’s no planning, predictive modeling, sales goal targeting or quantification of any kind that can eliminate or overcome this uncertainty. The customer will choose between all the alternatives available, including to buy nothing at all. It’s all contingent, and there are infinite possibilities. Firms choose their path towards facilitating the customer’s value experience, but there are no objective certainties.

So if business is not objective, quantifiable, or plannable, how would we describe it?

The philosophical word is subjectivism. Businesses would be better equipped for marketplace success if they followed subjective methods. They’re dealing with people and their emotions and their interactions with others in a complex social system. There’s no hard science, no spreadsheets, no data set that can predict the outcomes. 

That raises the question, what are the skills for business, if they’re not numeracy and hard science and mathematical economic. The answer is empathy. The skills of empathy – the ability to see inside customers’ minds and simulate a view of the world as they see it, to imagine what they are imagining, to reconstruct their mental model as opposed to imposing your own – are the most important in every business, and for every individual in every position and every function in business. Everyone must display customer empathy. What is the experience they are having? What’s imperfect about it from their point of view? What might result in a better experience for them, a potentially greater satisfaction for which they might be willing to pay. This empathy is best exercised at the level of the individual customer. If a business can get the empathic diagnosis right for one business, then they can investigate how it scales. Every customer is different, but there might be some patterns of response and interaction that spread out among a population of customers. 

Empathic diagnosis can reveal customers’ intent. What ends are they aiming for? What’s the highest value they seek? How can the firm’s proposition stimulate them to believe that it might contribute to that highest value? Uncovering the customer’s intent can indicate what experiments to run to find out whether any of the propositions a firm is able to get customers to imagine a future where new value is a possibility for them. Experiment is a key word: there’s no certainty in advance. Possibility is another key word: there is a wide range of possible outcomes. But by running the experiments and responding to feedback, the number of possibilities, the range of uncertainty, can be narrowed.

Once the results of experiments are in, then the firm can start unleashing its quants to do the economic calculation. How much will the customer pay based on these experimental results? How many customers might there be? How frequently will they buy. How much advertising budget should I spend to make the value proposition more widely known. Quantification is appropriate for these questions, once the empathic diagnosis is authenticated. 

Of course, the quantification can’t be accurate, and circumstances will change. It’s subjective calculation – the right method for an uncertain and subjective world.

Raushan Gross: Socialism Cannot Work, Not Even in an AI-Driven Economy

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Many of us seek products and services from sellers with goods of the best quality and relatively lower prices. Sellers seek the highest prices for selling the least amount of goods. Sellers compete for customers but would much rather be the only seller in the marketplace or market space. Furthermore, consumers want more for themselves and less for other consumers.

This depiction of market behavior is normal and may seem chaotic to some who view the marketplace through a socialist lens. With all the recent talk about reining in artificial intelligence (AI), taming AI, and limiting its uses, it sounds like the hubris of socializing artificial intelligence products and services.

However, an AI-driven economy cannot be socialized by a single entity, despite all the noise about AI restrictions, limitations, and tighter rules and regulations sent down from the top elites. We all use artificial intelligence in daily activities, ranging from work and leisure to side hustles, if you have one. With the glitz and glamour of technology, particularly artificial intelligence, the point that is missed is this: AI products and services enable firms to meet demands, assist entrepreneurs to create value, and enhance the exchange processes we all take part in daily.

Zack Dugow, who wrote “How to Defend Yourself against All-Powerful Monopolies That Control Your Business” for Forbes, made an important observation but did not take it to its logical conclusion. Dugow said, “If you have a heavy reliance on one of these monopolies [artificially driven software or social media/web page tools], you need to be able to pivot your business quickly and have your backup plan readily available to you. What service providers can you switch to?”

Should AI technology and AI startups eliminate monopolistic behavior between firms and consumers and rid the market space of the unrealistic notion of any socialization of AI technology? Everything has a price and a cost, which is why socialism was debunked some time ago.

However, what about artificial intelligence? Can it be socialized in the market space? You can socialize some things, but artificial intelligence cannot generally be owned and operated by a single entity or widely restricted from public usage. Someone must own the productive resources, sell services, and upgrade and maintain the hardware and software.

Opening market spaces for AI seems reasonable; however, will the elites plan to socialize AI services and products, close up the industry, and eliminate AI buyer options? When prices, inputs, and outputs are calculated, it becomes an unfeasible proposition that AI services, products, and industries be socialized. Fortunately, more and more AI service startups are available for buyers. Again, people use AI-enabled services and products to a large degree for many day-to-day activities. AI startups are on the rise, and they are listening to the market space, despite the socialist view that permeates throughout the media pushing toward more regulations and clamping down on open competition. Nevertheless, even in an AI-driven economy, socialism still cannot work.

No company has yet been granted exclusive ownership privileges of AI products and services. Not yet! Currently, there are over thirteen thousand (and rising) private startups of AI services and products in the United States alone, according to eWeek. Will artificial products and services remain decentralized? AI is a tool and enabler of exchanges between customers and firms. The advent of AI technologies can ward off monopolist behavior in a free market because, with an innovative approach to a consumer product or service, any company may be able to prove themselves worthy in the face of Goliath. Contrary to popular opinion, firms that use AI to enhance customer satisfaction and increase productivity open more doors for regular folks to start up their own business, which gives buyers more options in the marketplace. It also allows customers to enjoy the many features and benefits of products and services that add value to their daily lives. Some need to see this point. In other words, those who want to centralize AI services and products to one seller and raise the barriers to industry entry are saying out loud that they want more for themselves and less for you (and me).

That means no firm should have the exclusive privilege of being the only provider of AI services. Right? So many industries started as decentralized firms and are now privileged providers. Question: Who sets the prices of AI services, packages, and models? While your local utility provider, in many cases, is granted the privilege of being the only supplier of utilities, Amazon, on the other hand, has not received the same privilege. Amazon has a strong position in the market, but we know of competitors out there we can visit if we would like to. The difference between privileged providers and Amazon is that Amazon is subject to market competition. Therefore, they must listen to customers and pay attention to price increases, warehouse logistics, and customer service improvements.

If AI products and services remain decentralized, it will allow the market spaces to regulate the prices and costs for using AI services as opposed to if AI services are centralized under one firm or an elite few, similar to airline companies. When consumers and entrepreneurs see the rising costs of AI-enabled platforms, it reduces the incentives to use that technology, but it also allows new entrants to come into the market space and attempt to deliver a better product at a marginally better price. To disregard this market movement is the intent of socialism in general.

Furthermore, a handful of AI service providers eventually reduces the quality of this handful of providers (there are many instances of this decline in quality and rising price when a provider is granted a monopoly privilege). However, a natural monopoly might be reasonably valued. Technology of any kind, operating in a free market, should be the mechanism by which people who desire to enter an industry can do so with their skills and investment and make their attempts at competing—even if they are unprofitable, they were able to enter the fray.

What is often misunderstood about monopoly and prices is explained by Murray Rothbard:

There is no direct control over price because price is a mutual phenomenon. On the other hand, each person has absolute control over his own action and therefore over the price which he will attempt to charge for any particular good. Any man can set any price that he wants for any quantity of a good that he sells; the question is whether he can find any buyers at that price.

In a free market, no one is granted monopoly privilege—a privileged market position is earned by providing the best quality and price that consumers are willing to buy. On the other hand, forced or restricted choice is a form of socialism, or at least interventionism. At this time, it seems the capital markets are deciding where to invest, which is apparent in the rising number of firms producing more products and services so that businesses can meet public demand. If, however, all capital for AI investment funnels to one entity, it would be a disaster insofar as an economic calculation.

The idea of socialism does not hold up to its tenets considering AI’s technological advances made in recent years from the rising number of firms, especially advances in AI for entrepreneurs and consumers alike. A socialist vision of the world is very compelling, but reality tells us something different. The basic premise is that someone has to produce, someone has to consume, and there is a price calculation for both to exist. In the reality of socialistic visions, when subjected to market space examination, this premise tends to break down.

In many cases, the producer and consumer are the same people at different times. Production must take time, and with knowledge of prices, producers know the quantity of goods to produce at any given time. Even if one can socialize the production of luxury items, homes, and vehicles, how does one produce the capital required to make those items? Even with all needed inputs, AI cannot engage in the economic calculation needed to make a socialist economy work.

Author: 

Raushan Gross

Raushan Gross is an Associate Professor of Business Management at Pfeiffer University. His works include Basic Entrepreneurship, Management and Strategy, The Inspiring Life and Beneficial Impact of Entrepreneurs, In Pursuit of an Entrepreneurial Culture, and Emerging Institutions of Entrepreneurship. His research interests include topics ranging from entrepreneurship, free markets, economies, markets and competition, and the role of technology in market coordination.  

In Business, Aim At Benefits Not Goals.

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The beauty of Austrian economics is that it can understand the joy of an individual successfully making a sale as well as the computation of GDP, and the despair of losing a job as well as the calculation of the unemployment level in the economy. This is subjectivism: the understanding that the things that matter are subjectively determined by individuals and their interactions with others. The outcomes may be observed and aggregated but that doesn’t change what’s important to people.

Such an understanding should change how we think about the economy. The purpose of the economy is not to produce GDP, but to produce well-being. That’s a feeling, not a number. It can’t be quantified or expressed in dollars. The state of the economy is how people feel about their economic and personal well-being. It’s possible that some kind of a directional indicator could be produced by a survey – asking people how they feel and monitoring the trend (feeling better or feeling worse). The University Of Michigan Index of Consumer Sentiment attempts to do exactly that, and may be our best indicator of economic conditions.

There are broad implications of the subjective approach – let’s call it the people-first approach – to economics 

Mathematical economics is all wrong. In the twentieth century, the study of economics was hijacked by mathematics. The route to getting an economics Ph.D. or any kind of a degree, the route to formulating economic policy, and the route to managing businesses were all mathematicized. Mathematical laws of cause-and-effect were conceived as applying to human economic interactions. If an equation could be solved, then we could understand the underlying economic issue and take appropriate economic action. This whole approach omits the human element. There’s no equation for well-being.

Economic policy making is all wrong. Economic policy making aims at economic outcomes to be achieved through top-down planning. It’s government intervention in the economic interactions of individuals. Whether it’s taxation or tariffs on trade, or industrial policy (which industries government favors and those it restricts), or anti-trust, or money supply, or income redistribution, or government spending of any kind, it’s all directed at numerically-defined goals using input equations to predict numerical outcomes. That there is even a category of behavior designated as economic policy is a horrible distortion of the reality of the sources of economic well-being.

Our concepts of business management are all wrong. When commentators and the business media aim to assess companies’ performance, or their quality, or their merit, it’s always couched in mathematical terms, whether that’s stock price trends or revenue growth or profits. When CEO’s and executives and managers talk about their achievements, it’s also demonstrated through numbers. It’s rare to hear a CEO talk about the feelings of their customers. Yet it’s those feelings that should be the drivers of corporate behavior and the logic of corporate decision-making.

All of these errors involve goals. We set goals, we aim at goals, we measure whether we met, exceeded or fell short of goals, and by how much. These are all mathematical calculations, numerically enumerated. There’s no subjectiveness or well-being. This kind of calculation has its place in science, which has the extrinsic perspective of trying to understand and predict the material world we live in. We look for scientific laws to explain what has happened in the past and predict future happenings. But this kind of scientific method is inapplicable to the individual, personal, emotional, illogical interactions of humans in their economic dealings with each other. if a shopper feels that a store has an attractive price for potatoes but refuses to shop there again when the checkout clerk is rude, the outcome can’t be modeled. Will the shopper pay the price for potatoes and tolerate the rudeness? Or pay more for potatoes elsewhere, where the level of friendliness and politeness is higher? Will they tell all their friends about the rude service and aim to persuade many more people to change their shopping habits? Will they change their mind at a later date and return to the first store to shop because they eventually decide that low price overcomes rudeness at the checkout? None of this can be modeled and mathematicized.

The solution is to substitute benefits for goals, and to aim at delivering those benefits rather than numerical outcomes. Value is a subjective experience for users, and the idea of benefits is to facilitate that experience by describing the betterment available from accepting a value proposition – feel more chic in new fashions, enjoy speed and safety and green credentials driving a Tesla, make your business operations more efficient and effective using new software, take new confidence in your organizational design with this sound consulting advice. Businesses are better advised to aim at delivering the right benefits rather than aiming at revenue or unit sales goals or returns on investment. These results will be outcomes, but they shouldn’t be goals.

If businesses were benefit-focused, they’d concentrate on knowing their customers as well as possible, on understanding those customers’ needs and wants and preferences. They’d aim at facilitating well-being in individual lives and therefore in the economy.

The Financialization Of The Economy Distorts Our Understanding Of The Entrepreneurial Ethic.

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We have been led to think of the economy in financial terms: the stock prices of the largest companies, their quarterly earnings reports, trends in GDP, mergers and acquisitions, central bank money-printing and the prices of homes. This phenomenon is a reflection of the expansion of the financial sector of the economy – the investment banks, the brokerage houses, the stock markets, the hedge funds and the ETF platforms. But when the financial sector expands, it does so at the expense of the productive economy. More and more smart and talented people are engaged in trading certificates and designing derivatives and fewer and fewer are engaged in production of real goods and services.

Financialization makes the case that business and management are all about driving stock prices up, conducting arcane financial maneuvers like manipulating debt offerings, and finding new ways to trade financial instruments. It even has its own ideology: maximizing shareholder value.

For example, the notion of stock buybacks has become popular among the high-flying companies of this financialized age. Apple is a prime example. There are years in which Apple has spent more than 100% of its net earnings on buying back stocks from shareholders, thereby providing those individuals with a major cash bonus. Of course, a significant group to benefit from this action are those members of management who hold stock grants or stock options, which they buy back from themselves at a high return. 

Stock buybacks are self-serving stock price manipulation.

As Professor William Lazonick has pointed out, very famously in an article in Harvard Business Review under the title Profits Without Prosperity, but also in many books, papers, and an open letter to the SEC, this action of stock buybacks undermines capital formation – companies spend their earnings on stock buybacks that help share traders, and underinvest in the capital that makes workers more productive and generates value for customers. Financialization in the form of maximizing shareholder value through dividends and share buybacks has distorted the true purpose of the firm, which is to facilitate value for customers, earn cash flows in return via the customers’ willingness to pay for that value, and to reinvest the earnings (cash flow minus cost) in more capital to facilitate more customer value.

Since it is so lucrative to manage a company that’s traded on a stock exchange, this form of financialization has led to a second-order distortion. Start-up businesses funded by venture capital and private firms seeking to monetize their growth by sprinting toward an IPO, i.e. for their stock to be traded on an exchange. The business model is to grow at a fast pace, at the expense of maturing a business model, or refining the value proposition through customer feedback. These companies “burn cash” – i.e. make operational expenditures far in excess of cash flow from sales to customers – in order to establish a price for their privately traded shares that could be translated to be a successful IPO. Examples like Uber, WeWork and Peloton show the many ways this financialized approach can fail, when growth is not underpinned by true customer value creation.

The True Entrepreneurial Ethic.

The greatest damage that financialization has done to capitalism is to distort our views of the entrepreneurial ethic that underlies the system. Many young people think that capitalism is exploitative and cynical, which is not an irrational view when confronted with corporate executives who award themselves stock grants and then implement stock buybacks to cash in on the stocks they awarded themselves. 

The reputational damage to free market capitalism is worsened by the association of the term “entrepreneurship” to the burn-cash-in-a-dash-to-IPO tactics of startups and Silicon Valley unicorns. Their behavior is not that of entrepreneurs. True entrepreneurship is the identification of a market opportunity defined as an unmet customer need: a customer’s unease about the status quo, the feeling that things could somehow be better than they are, without a specific idea of how to realize that betterment. The entrepreneurial business is the one that comes up with the welcome new way to relieve that unease, and to actually make the customer’s life better, as defined by their own subjective evaluation. If the entrepreneur gets it right, and does so better than any competitor in the eyes of the customer, then they trigger a willingness to pay for value received. Willingness to pay becomes cash flow, and if the cash flow is greater than the entrepreneur’s cost, there is profit to be reinvested in capital for more and even better services in the future. The ethic is to serve customers, and to accept the rewards of the market for doing so. 

If the owners and managers of the entrepreneurial firm get rich, it’s from an abundance of customer satisfaction, not from stock manipulation through share buybacks. They’ll accumulate capital, because capital is defined as assets that produce customer value. The more customer value they facilitate, the greater the value of the entrepreneur’s assets. That’s why entrepreneurial businesses reinvest most of their business’s profits to create more capital value in the future.

This entrepreneurial “flywheel” (as it’s characterized at the very entrepreneurial business known as Amazon) can be a virtuous cycle: serve more customers with more and better offerings, receive more cash flow, and reinvest the profits in new capital formation in order to serve more customers in better ways. Entrepreneurship raises all boats, and does so through the explicit purpose of serving customers’ needs.

The financial sector and the stock traders and stock sellers who think of business only in financial terms do entrepreneurial capitalism a great disservice.

Socialism favors big business; capitalism is entrepreneurial.

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The Road To Socialism And Back is a fascinating real-life case study from the Fraser Institute about the differential impact of market capitalism and socialism on both production and consumption. It focuses on Poland, which had been a free market economy until the Second World War, then transitioned to a Soviet-style centrally planned socialist economy under USSR hegemony, and then transitioned back again after 1989 to a market economy.

There are lots of eye-opening statistics to highlight the impact of a socialist economy on the lives of consumers. For example, there were only seven telephone lines per 100 inhabitants in Poland in 1986 compared to 33 per hundred inhabitants in nearby Greece, and approximately 50 per household in the USA. The wait for housing was up to 30 years, twice as long even as the Soviet Union. The number of cars per 1000 people in 1980 in Poland was 64, compared to 350 per 1000 people in Switzerland at that time. GDP per capita in 1986 was roughly $2000, compared to $19,282 in the USA.

One of the observations in the Fraser Institute report is the socialist Polish economy was dominated by big businesses, which were heavily subsidized, and small and medium-sized businesses were discriminated against. 

The investments in a specific year were determined by the long-term plan and current projections of growth. These investments were generally directed at the capital goods industry and heavy industries, especially steel, chemistry, and coal, at the expense of the consumers’ desires (Piatkowski, 2013). The few, predominantly agricultural, private firms that did exist were deprived of financial resources available to state firms, thereby constraining private firms’ abilities to compete with state companies.

The favored large state companies were given increased subsidies and favored access to more resources whenever they missed their production quotas. The logic was that the production target was everything in the central plan, so more resources must be granted to the large firms theoretically capable of delivering it, especially when they fall short.

This adversely affected both the quantity and quality of output. The problem got worse over time as the least profitable industries in Poland received the most financial support and attracted the most workers, siphoning resources away from more profitable enterprises. And if the experience of Hungary is any guide, firms with the most political clout (as measured by the size of fixed assets and employee involvement in the party) received the most aid. Large firms dominated socialist economies. While construction firms with 500 or more employees were only about 16 percent  of the industry in capitalist economies, they represented over 70 percent of the industry in Poland and other socialist countries. 

When Poland transitioned back to a market economy, most notably after political changes in 1989, many of these large firms with negative value-added production went bankrupt when they faced competition in the absence of state-supplied loans and subsidies. That is, the value of the inputs that these firms used was higher than the value of their outputs, indicating inefficient production. 

Economist Ludwig von Mises had a simple insight which the socialist central planners ignored or misunderstood: close their eyes to the economic problem: the capitalist system is not a managerial system; it is an entrepreneurial system. Capital can only be efficiently allocated when consumers and customers are free to signal what goods and services they deem most valuable, and when producers are free to allocate and reallocate capital to those most valued uses and thereby, through market-sensitive capital allocation, compete for the customer’s dollars. 

Socialist central planning cannot respond to these signals, and in fact, represses them. But the favoring of the biggest corporations, and their failure to respond to market signals, is not entirely limited to socialism. Western capitalism has been favored by the rise of entrepreneurially-owned and led firms who brought new capital combinations to market, harnessing new technology to bring new benefits for which customers clamored. From John D. Rockefeller’s Standard Oil, which brought affordable illumination to homes across America, extending their days and their family time and expanding their productivity; to Henry Crowell’s Quaker Oats company who brought those families safe, wholesome and nutritious food; all the ways to today’s Elon Musk, saving the planet with electric cars and solar power – entrepreneurially-led companies have shown the way to prosperity by starting small and growing because they served customers and thereby attracted capital.

But there is a danger that when corporations get to be large, they start to face the same inefficiencies that dogged the Polish socialists. Big companies start to develop their own central planning units (it’s called strategic planning or budgeting, but it’s the same in principle), they grow large bureaucracies that are not producing but constraining production, they resist innovation to protect their existing businesses (it’s called defending market share), they lobby government for subsidies and regulatory or legislative protection, and they misassign capital to activities such as dividends or share buybacks instead of investing in future innovation.

Happily, Mises’s insight always applies. There will always be innovative entrepreneurial firms to ensure that the capitalist system is driven by market preferences and not central planning. There will always be a Tesla to beat General Motors, and a Walmart to beat KMart, a Netflix to beat Blockbuster and a Microsoft to beat IBM. And in time, as those entrepreneurial firms mature, they’ll start to show symptoms of misallocation of capital (Apple, for example, is notorious for its excessive use of share buybacks to allocate capital to share traders rather than innovation) and new entrepreneurial insurgents will take their place.

It’s not only socialist economies that suffer from the inefficiencies of big firms. But in the capitalist economies – so far – there’s always entrepreneurship to provide competitive balance and refreshment of the capital stock.