About ten years ago I began teaching entrepreneurship at a university, which lead to the realization that I needed to study more about entrepreneurship. The study of entrepreneurship still continues, but I have expanded my study to include learning and complexity. These three themes are actually part of an integrated whole, if one considers Henry Mintzberg’s concept of emergent strategy, but today I just want to discuss entrepreneurship and complexity.

To set the stage, let me define entrepreneurship and complexity. I think Harold Gardner at HBS defined entrepreneurship well as “entrepreneurship is the pursuit of opportunity without regard to resources currently controlled”. The focus on opportunity and the challenge of mustering resources in order to execute frames the issue well. I might have added the concept of “scaling” in the definition of entrepreneurship, but most traditional economists do not. “Complexity” is a dynamic system where variables are inter-related but uncertainty from lack of information prevents deterministic analysis. Uncertainty here is Frank Knight’s definition, which to paraphrase is “a situation where you lack sufficient information to determine probabilities”. (For Knight “risk” was a situation where you had sufficient information to determine probabilities.) Deterministic analysis is the type of mathematical analysis that one finds in operations research, financial modeling and most planning disciplines. So to summarize, complexity is an uncertain situation not subject to deterministic analysis for lack of sufficient information about the inter-related variables.

What lead me to ponder the relationship between entrepreneurship and complexity was the fact that entrepreneurship is a classic example of the inter-related variables inherent in complexity. However, much of the analysis in entrepreneurship is deterministic. So how does one reconcile the uncertainty of complexity with the deterministic, mathematical analysis so common in entrepreneurship and business? Fortunately economic theory provides most of the answer. It just took me awhile to put it together.

If we think about entrepreneurship, we can break it down into two concepts—opportunity and execution. Opportunity or market opportunity sets the theoretical size of the company and execution dictates whether the company scales, fails or suffers along at below its potential. Execution can be further simplified to two basic concepts—product development and sales. Effectively, the company needs to develop repeatable processes to source, manufacture and distribute the product. Repeatable processes also explain the approach to product/market fit initially and at scale, which allows the company to successfully satisfy the needs of the customer. These repeatable processes, what we can consider as optimization problems, are where the mathematical analysis applies. One could probably argue that if the process is not repeatable, the mathematical analysis would not be reliable. To put it another way, repeatable processes provide sufficient information to determine the accurate probabilities required for mathematical analysis. It all looks so deterministic, so where does the complexity come into entrepreneurship?

If we return to the product development-sales framework, product development governs the relationship with suppliers. As the entrepreneur adjusts the product for any of a myriad of self-interested reasons, the suppliers of goods or services are “shocked” in economic speak and forced to act in their self-interest. However, we lack information sufficient to determine how the suppliers may react and therein we find the complexity. In the sales framework, imagine the entrepreneur raises prices. We lack sufficient information to determine how the customers, the competition, the press and perhaps even the government will react. Again, the “shock” of the price increase allows complexity to manifest itself. "Economic phenomena like prices are the unpredictable result of the complex mutual adjustment of millions of individuals" [1] acting in their self-interest.

The shocks described here are the normal shocks of supply-demand--the allocation of market resources--and the related information travels over a peer-to-peer network of linked individuals including suppliers and customers. This peer-to-peer network extends the shocks and the complexity and leads to what Brian Arthur at Santa Fe Institute calls the perpetual invention of the economy … and the entrepreneur. This perpetual invention would be called evolution if we were studying biology.

The next subject for me to explore is the role of networking in economic shocks. May have to go back and re-read Sandy Pentland's "Social Physics", an excellent book on how networks really work.

Further reading that influenced this article and my thinking on entrepreneurship and complexity:

- Complexity Economics: A Different Framework for Economic Thought; W. Brian Arthur
- The Capitalist and the Entrepreneur (Chapter 5, 6); Ludwig von Mises Institute (Available in PFD version)
- Economies of Scale, Economies of Scope;
*Ribbon Farm*; Venkatash Rao - Classical Liberalism: A Primer; Institute of Economic Affairs [1]