Economic evolution is often a topic in conversations with the teams I am coaching and the leaders I advise. It is a simple idea to explain, yet it allows for a much deeper exploration of why and how economies and organisations change. Even leaders without a background in economics or innovation can see the role they play in promoting innovation and economic development.
Evolution is a general-purpose and potent algorithm for finding innovative solutions to complex problems. It describes a naturally unfolding process in the economy that plays out at different levels as people, individually and collectively, search for and try new ideas or modifications of what they already know. At its core, evolution is an iterative process of creating variety and selecting designs that are fit for purpose and then amplifying these by adapting resource flows. While in nature, fitness is determined by the environment, in economies, fitness can be intentionally influenced by human actors.
The idea that economies evolve continuously is not new. The term “evolutionary economics” was coined by Thorstein Veblen (1857-1929) already in 1898. Earlier, Karl Marx and Adam Smith raised issues that are now seen as part of the evolutionary economics school. Joseph Schumpeter’s theories of economic development had a strong evolutionary perspective. Possibly the Schumpetarian idea that is best known beyond economics is his suggestion that entrepreneurs introduce innovations that creatively destroy the equilibrium created by the predominant arrangements. Much later, Richard R Nelson and Sidney G Winter’s book An Evolutionary Theory of Economic Change (1982) was a seminal work that marked a renaissance of evolutionary economics.
Below is a simple illustration of the evolutionary algorithm.
The evolutionary algorithm works as follows:
- An innovator or a team creates some variation based on existing ideas. The new idea is often created by recombining what is already known (knowledge and technology is cumulative) with some new insights. Or perhaps they figure out the idea based on their understanding of a given situation (experience is also cumulative). It may even be that the variation is created through serendipity. The critical point is that the variety of possible solutions or stock of ideas increases, irrespective of whether there is currently demand for any of these ideas. For the variation stage to be complete, the idea must either be recognised by the innovator as worthy of further pursuit or knowledge of the variation must spread to others.
- A few pioneering buyers, managers, investors, or other innovators then select an idea because it can address a need, or solve a problem, or plugs a gap in a given context. Selection implies that resources, attention or access to complimentary knowledge or networks are made available, leading to the concept’s further development. Choosing an idea that is different and unproven is a risk, but the people making the selection somehow recognise the idea’s potential or the limitations of existing alternatives. Innovative ideas are often further developed because they are selected. My late business partner Jorg Meyer-Stamer constantly reminded me “that technologies become efficient because they are chosen; technologies are hardly chosen because they are already efficient”. As the idea attracts more resources, funds, interest, talent and pioneering buyers, it becomes easier for others to select it as the concept is refined. At this point, other innovators may enter and create more complimentary variety, which makes selection even more likely as the ecosystem of related and complimentary solutions becomes more established.
- At a certain point, the idea becomes amplified in the economy or the system beyond the ideas or designs of the original innovators. Where those doing the selection in the previous phase were taking a risk, in the amplification stage the risks are much lower as the innovative idea is understood better, is more credible and has more support.
This evolutionary algorithm plays out in the marketplace and is fuelled by incentives that shapes each stage. It also plays out within organisations where different ideas compete for resources.
There are ways that we can shape the incentives in all three phases of the algorithm.
- We can figure out what incentives dampen variety creation or which incentives can be amplified to encourage learning about and exploring possible alternative arrangements.
- We can explore how we can tilt selection incentives away from innovations that are less desirable towards more desirable solutions.
- We can explore how good ideas that have already been selected (and thus developed) can be amplified.
I know that the incentives are often understood to be financial. But remember that recognition, being able to contribute, using one’s talent or simply solving a puzzle are also important social incentives. In the same way, fear of failure or ridicule, not having the resources needed, or not having the time or the permission to solve a problem are incentives that hamper innovation.
I want to end this post with just a provocative question. The institutions in our economies and the rules/cultures in our organisations are already shaping the algorithm. What innovations and alternatives are the algorithms in your system incentivising, selecting and amplifying? I would love to hear your reflection on this question.
If you do not want to post it in the comments, then send me an email or reach me on twitter.
Credits: The ideas in this post are inspired by many conversations with Marcus Jenal over the last ten years. In 2015, we had the privilege of deep diving into evolutionary thinking and its applications to economic development in a project funded by the BEAM Exchange. The ideas we have explored together have shaped my view of organisations, markets and how societies evolve.
