Category: Evolution

How institutions, technologies and companies co-evolve

This is the fourth post in this series about economic evolution. In this post, I will look at the co-evolution between companies and the broader institutional environment they form part of.

Towards the end of the 2nd blog, I mentioned that the design spaces within firms (and organisations) interact with different design spaces beyond their boundaries. The available “technology” modules within any organisation, private or public, interact with and are shaped by technology the modules available in the institutional landscape. The technology in the preceding sentence should be understood as “knowing how to do or achieve something specific consistently”. For example, think of the trust system needed for two companies to transact with each other. Perhaps they rely on the social institution of social relations. This worked for most economies for a long time. But with increasingly sophisticated products and services and also the more impersonal nature of many transactions, contracts and their enforcement through a legal system is increasingly important. To further make impersonal transactions smoother, standards, performance criteria and branding are all social institutions that have evolved to enable transactions.

These institutions, including the norms and the organisations that provide related goods and services, evolve with the economic transactions they enable. In some cases, the institutions lead the evolution by providing the economy with new knowledge modules or services. In other cases, unmet demand might lead to an institutional response. Yet in another case, policymakers might design policies to shape the institutional offerings or the demand patterns.

The broader institutions and economic activity co-evolve.

I want to take this further by focusing on the meso space and how this space co-evolves with industries, locations or communities.

The meso space is a design space where interventions are designed to address the persistent patterns in the economy. Most microeconomic transactions occur via markets, hierarchies or networks, and each of these forms of allocation have strengths and weaknesses. All three can fail. When a particular kind of failure persists, this can be called a market failure, management failure (for hierarchies), government failure (in the case of public services failing), coordination failures or systemic failures. The meso space is where stakeholders intentionally intervene to address or respond to persistent failures.

Because it is sometimes not helpful to use labels like market or government or systemic failures, we often describe these patterns as “patterns of underperformance”. These are the patterns we often see when we look closely at an industry, value chain, location or national economy.

Some meso interventions may be targeted at a particular industry, a technology, a region or a specific pattern. In contrast, others may target whole policy areas like industrial, technology, trade or locational policies. While most meso interventions are supposedly intended to deal with negative or problematic patterns, there is no reason that meso interventions can also be designed to leverage positive characteristics. That is exactly what many tourism or investment promotion strategies aim to do.

Meso interventions might be a policy, project, programme, service, or organisation. Sometimes an existing organisation might launch a new service or provide additional functions to address a particular pattern of underperformance in the economy. This, in turn, might result from a particular ministry deciding to create a policy to address a particular issue, like deciding to invest in an incubator to develop particular solutions the company might be interested in. I know this might sound unclear, but when a policy or strategy is specific in its focus, we describe it as a meso instrument. In contrast, macro policies and strategies are more generic and are not specific to an industry, technology or location.

The public sector is a dominant actor in the meso space. However, in most countries, the public sector does not act like one stakeholder. There are different government departments and publicly funded agencies, at different levels, all with different jurisdictions or mandates. Just like coordination failures can occur in the private sector, coordination failures within different public functions can paralyse a country, industry or location.

However, not all meso policies and interventions are about the public sector trying to be the benevolent private sector supporter. Companies can also design policies that shape the economy around them. For instance, a large manufacturer might have policies to develop their supplier networks, to make the location where they are based more attractive, or to support particular public interests. Not-for-profit or non-governmental organisations can also have development policies to address particular economic patterns. So meso policies and programmes can be designed or implemented by the public, private or civil sectors.

While some economic development practitioners are often biased in favour of addressing market failures, the meso space must often also address government and other systemic issues. For instance, the meso space is often critical to designing or implementing programmes to reduce inequality, provide more effective public goods, reduce coordination problems, maintain and expand critical physical and digital infrastructure and address other social priorities.

Suppose a persistent pattern of decline plays out in a location or an industry over time. For instance, let us imagine that the city centre and its key economic activities are in decline. It is unlikely that this pattern of decline can be addressed by only the public sector implementing a few projects. Most likely, the pattern can only be arrested by mobilising many different public, private and civil organisations and then pursuing projects together for extended periods. Interventions aimed only at the private sector are unlikely to work by themselves, as renewal and investment in public organisations, civil and social infrastructure would mostly likely also be required. The location will change as the economic activities of enterprises and the supporting institutions co-evolve. In most cases, this is a process that takes time.

This example illustrates how industries and institutions co-evolve. As the city centre declines, social institutions and networks might also decline. At the same time, new informal economic activities might arise in the place, but this might lead to an acceleration in the decline of formal economic activities. Renewal in public, private and civil organisations might be needed to reverse this trend. At the same time, investments in public infrastructure and attracting private investment are needed. These kinds of initiatives will shape the incentive landscape for investors, individuals and entrepreneurs, just as the kinds of investors, individuals and entrepreneurs might play a role in deciding where to start or what to do.

It is impossible to fix persistent patterns of underperformance in the private sector through the private sector alone. This is at the heart of systemic change: the recognition that firms and their meso landscape of interventions, programmes and organisations co-evolve. Sometimes we start with the firms and then try to invigorate the meso landscape. At other times, we may start with the meso landscape and try to make it more resilient, innovative or valuable to the private sector, the community or the location. But we also have to think both of the micro level where transactions take place via markets, networks and hierarchies, as well as the meso landscape where incentives, investments and coordination takes place. Any systemic intervention would typically involve coordinating the development efforts of the public, private and civil sectors over extended periods.

The challenge is that co-evolutions are not designed ex-ante, although it is possible to catalyse changes in the public and the private sector if there is enough willpower and incentives for change. Every small change creates further opportunities for change by making knowledge or technology modules available. Any idea or modules that become available in the economy, even if it was meant for a specific purpose, becomes part of the substrate of ideas that others can use in new combinations to innovate or transact. This may lead to a further changes in public policies, or to further changes in the institutional landscape, which in turn may lead to additional services or technologies becoming available to the economy.

This is how industries, institutions (both norms and organisations), technologies and locations co-evolve. They contribute knowledge modules or functions to the economy, that others can combine with to create value. And so it goes on.

If you think of the context where you are working, can you see examples where changes in the private sector (performance) lead to changes in the meso landscape or the other way around? Where did new or adapted services from the public meso programmes shape a location, industry or technology? Can you think of any unintended consequences or benefits, in other words, that was not designed intentionally but happened because of preceding changes?

Alternatively, where did changes in the private sector result in adaptation or changes in the public sector?

Lastly, can you think of examples where a civil or not-for-profit organisation’s behaviour (or interventions) resulted in public and private sector changes? How did the system co-evolve as a result?

You are welcome to share your thoughts in the comments below. Or just continue sending your comments to me by email or social media. I value your comments and suggestions.

Image credit: Image created by DALLE on 22 February 2023. The prompt was to create a drawing showing the relationship between urban planning and universities.

The modules that evolve

This is the third post in this series about economic evolution. In this post, I want to focus more on the modules that the evolutionary algorithm act upon that I mentioned in the previous post.

Ideas are the most fluffy evolutionary material that spreads between people and organisations. These ideas spread via formal means (like education, formal communications, management decisions or regulations) but also via less formal means like the media, stories, people moving between places and social networks. We pick up ideas as we move around in society, and often we combine these ideas with our own to create completely new idea combinations. I always ask people I interview where they got their ideas for innovations from, and I have heard the most amazing stories of how they took an idea developed in a completely different context and made it work in their own situation.

Tracking how ideas spread in society is tricky, partially because we cannot always remember where we heard or saw something that triggered a thought.

In the first post, I explained that Nelson and Winter (1982:14) preferred to use “routines” instead of “ideas” in their theory as the material that the evolutionary algorithm act upon. Routines are relatively stable ways of arranging physical and social technologies to perform certain functions. Even if they can come about in an arbitrary form, organisations tend to replicate routines internally, and other organisations also copy and adapt routines that appear to work well.

Eric Beinhocker (see the 2nd post) argues for using “modules” as the primary material on which the evolutionary algorithm acts. He agrees with the co-evolution between physical and social technologies but adds that there is a third design space, namely business plans.

“A module is a component of a business plan that has provided in the past, or could provide in the future, a basis for differential selection between business in a competitive environment.” A module is made up of configurations of routines from the physical, social and business plan design spaces.

Beinhocker, 2007:283

Continuous decisions about the composition of these modules must be made in any organisation or company. These routines and modules can be pretty unstructured, but the theory holds that the better-performing modules will be replicated within and beyond the organisation. In contrast, the less-efficient modules or routines will become obsolete when replicated less. However, even inefficient or unproductive modules can persist due to stubbornness, sunk costs, pride or ignorance.

A challenge we face is that the many internal marketplaces (within organisations) where different concepts or module formulations are pitched against each other do not work effectively. In addition, companies relying on inefficient module configurations can still thrive in uncompetitive marketplaces because the markets cannot select better-performing alternatives.

Over the years, I responded to this issue through the instigating innovation series and my teaching at various business schools.

Those organisations that constantly develop or search for new modules or tinker with their existing modules because of anticipated changes in the broader environment can be described as having dynamic capabilities. Dynamic capabilities cannot be bought, it is built through the intentional behaviour of entrepreneurs, managers and employees. David Teece is one of my favourite scholars studying dynamic capabilities, and here is his definition:

Dynamic Capabilities are the firm’s ability to integrate, build, and reconfigure internal and external resources/competences to address and shape rapidly changing business environments. 

Teece et al., 1997, 1990

Teece must often repeat building dynamic capabilities is about achieving abnormal results over the long term. The capabilities part is about the investments in abilities, skills, routines and relationships that are enduring AND that are distinct from what competitors may be doing. The dynamic part refers to the ability to adapt and proactively create market conditions that favour the company. It is about an internal culture of change, experimentation and recognising what works (and what does not work). Why I took this detour is that we need to find ways to foster dynamic capabilities in developing countries in both the public and the private sectors. We have too few organisations actively trying to create new modules that are then adapted based on how they perform in the marketplace.

Back to the main thread. Investments in modules create path dependency, especially when all the investments are along a certain trajectory. In the software and services sectors, companies can change direction faster than in the manufacturing or public sectors. This is mainly due to the way fixed capital is invested in plant, equipment and infrastructure. Once committed to a specific configuration of modules, it may cost a lot of money to change direction.

Whereas routines can often be observed and replicated between companies or contexts, modules are often harder to observe and copy. For example, we can visit a factory and see some physical and social technologies arranged in routines. We can observe how raw material, processes, people and workflows are organised on the factory floor. However, the modular knowledge units combining physical, social and business plans are harder to observe or measure. The hidden parts include the internal incentive structure to innovate and resolve problems, the past learning about what did not work and should never be attempted again, etc., how the factory is connected to suppliers, clients and headquarters, and so on. Some parts of the modules are harder to observe because they weave together past decisions, strategies, funding mechanisms, and future expectations using combinations of physical and social technologies. The machine standing there or how people work together is just the visible tip of the module (or configuration of modules).

The irony is that even management may not realise how much tacit knowledge is involved in the logic that weaves the many different modules combined in a single unit of an enterprise in the modern economy.

From an innovation perspective, there is something else to note about how these modules are created, adapted and disseminated in economic system. The ability to identify, absorb, create and deploy these modules is cumulative. Think of lego bricks. The more modules a specific company has access to or has tried before, the more variations it can create, and the more creative solutions it can select to try in the marketplace.

When this happens over many companies in the economy, markets and users can select from more variety, and better ideas are replicated and amplified in the economy. We know from the research by Cesar Hidalgo, Ricardo Hausmann and the Centre for International Development at Harvard, that these winning knowledge modules can be mapped in the Productspace. (I have a hidden section on my blog site where I have documented some of my experiments and visualisations with this approach – you can access it here).

The experience of selecting combinations or transferring modules to other business areas is cumulative. Companies building modules drawing on different or technological knowledge are better positioned to create entirely new innovative architectures because they can draw on modules from divergent knowledge domains. In contrast, companies that can only manage knowledge modules drawing on narrow knowledge domains are more likely to become specialists. The narrower the range of modules, the higher the risk of being disrupted by other competitors that can build modules on a wider front.

It is not only companies and public organisations that build up these modules. Industries can build modules. Universities play a key role in introducing recent or reliable modules into society. Some modules are described in sufficient detail that can spread via blueprints, technical documentation or software code. Members of online communities can together develop knowledge modules in a distributed way. Just think of the power of Linux or other forms of open-source software that is developed in a distributed way.

Modules can also be accumulated in a society, like the knowledge of how to organise a certain kind of festival, or the modules accumulated through dealing with certain phenomena from the environment. When people change jobs or move from a workplace, they carry with them some understanding of the modules and their sub-routines with them. However, turning some of these modules into a business unit, product or process might require investment in developing the missing business plan areas.

In some locations, office parks or regions, knowledge about certain modules may be developed or may flow more easily over organisational boundaries. Of course, this process may be fostered by developing unique public (or private) infrastructure and through social networks.

I’ll go ahead and conclude. Entrepreneurs, managers, investors and public officials have to intentionally decide where to build modules in their organisations. These modules will typically combine elements from physical and social technology design spaces with business plans. Modules will evolve as they are selected by the organisation (management) and by the market. These modules are cumulative, those that have access to more can also create more variations. Those who draw their modules together from more divergent knowledge domains may have a long-term advantage over those who specialise in building capabilities in a narrower field. Dynamic capabilities are about intentionally investing in capabilities, and continuously evaluating, adjusting and refining existing modules with new ideas from beyond the organisation. Not all the modules originate in a firm, some are present in a community, or a network or are drawn from other companies or contexts. This is easier in some places than in others.

Some questions to explore in your own context:

  • In the industries or domains that you work in, what are the modules that you can identify?
  • How are they changing?
  • Who are the pioneers that are accumulating modules from divergent knowledge domains?
  • How do they compare to those mainly focused on developing modules in a narrower field?
  • Which public and private organisations have built up dynamic capabilities? In other words, they are constantly reflecting on their performance, and constantly working on building capabilities based on their understanding of their own situation in relation to changes in the broader context. How are these organisations managed, and how does their performance compare to more conventional organisations?
  • How are the accumulation and adaptation of modules fostered or promoted in certain areas, knowledge domains or industries?

Please share your thoughts in the comments, or drop me an email.

Image credit

The image at the top of this blog post was created by DALL-E of OpenAI. asked DALLE to create a picture of a topographical landscape with valleys and peaks.

PS.

Here in South Africa, we are all developing modules of how to cope with electricity blackouts (Our government calls it “load-shedding”, which is an excellent way of describing institutionalised incompetence).

Sources:

Beinhocker, E.D. 2007.  The origin of wealth. Evolution, complexity, and radical remaking of economics`. London: Random House.

Teece, D.J., Pisano, G. and Shuen, A. 1997.  Dynamic capabilities and strategic management. Strategic Management Journal,  pp. 509-533.

Teece, D.J. 2019.  A capability theory of the firm: An economics and (strategic) management perspective. New Zealand Economic Papers, 53.

Further reading:

If you have access to journal databases, you should also look up the fantastic work of Giovani Dosi, and also Richard R Nelson and B.A Lundvall.

Updated on 5 March 2023 with minor corrections

How technologies evolve

In my previous post, I introduced the general evolutionary algorithm of variety creation, selection and amplification.

I intentionally remained vague about what the evolutionary algorithm act upon by referring to “ideas”. In this post I will be more specific about what kind of ideas evolution acts on.

Nelson and Winter (1982) argued that the material that evolution acts upon are formal and informal routines:

“ We use this term to include characteristics of firms that range from well-specified technical routines for producing things, through procedures for hiring and firing, ordering new inventory, or stepping up production of items in high demand, to policies regarding investment, research and development, advertising, business strategy about product diversification and overseas investment. In our evolutionary theory, these routines play the role that genes play in biological evolutionary theory

(Nelson and Winter, 1982:14)

These routines could emerge through serendipity or they could be the result of the creative efforts of individuals or teams. They could originate in isolation, but very often they are combinations of old and new, or combinations of internal and external ideas tried in a local context. These routines could be arranged around particular equipment or processes, or they could be norms about how people in a workplace treat each other.

These routines become part of the technology available to the firm. Good ideas that seem to work better than alternative arrangements typically spread between organisations and teams through imitation, social networks or the movement of people. Sometimes ideas are spread by word of mouth, other times through text or the media, and in some cases through mimicking or copying (or reverse engineering). Sometimes a confluence of factors makes the same ideas or routines emerge in many different organisations at the same time. Think back to how we all had to figure out how to get our work done during the Covid lockdowns.

Within organisations, the ideas and the routines that are selected are chosen by how they contribute to the objectives of the organisation. For most companies, the contribution of these routines to profitability is important, but that is not the only criteria. External and internal incentives will shape what is deemed the selection and retention criteria. I have visited enough companies to know that profitability is not the only criteria. Within companies, there are marketplaces for ideas. If somebody makes an suggestion about an improvement or adjustment management and peers might select those ideas, or they may be rejected. But let me not digress.

Ultimately, all the routines and ideas that a company create, adapt and combine (through its internal idea markets) result in products, services and offerings that are either selected or rejected by external markets.

But we know that organisations cannot only achieve their objectives with routines. I again turn to Nelson and Winter (1982) who argued that there is a co-evolution between two different kinds of technological spaces:

  • Physical technologies are what we often think of as technology. It is the artefacts, equipment, infrastructure and even code that are used to perform a function or to harness natural phenomena to achieve a specific outcome. These technologies are methods and processes for transforming matter, energy and information from one state into another in pursuit of a particular outcome. A physical technology is not only an artefact, it also includes the designs, instructions and code needed to make it, maintain and use it. Physical technologies are typically modular and often interdependent on other physical technologies. For instance, my smartphone depends on other technologies to function like a mobile network and the electricity distribution system.
  • Social technologies are methods, designs and arrangements for organising people in pursuit of a goal or objective. Social technologies smooth the way for information to be exchanged, priorities to be set, or unexpected situations to be dealt with. Social technologies enable (or disable) learning and adapting to changes in the environment. Organising people into a hierarchy, creating and enforcing regulations or arranging marketplaces are all social technologies. Like physical technologies, social technologies are modular and cumulative. Each new knowledge module or routine that is created opens up new further opportunities for a variety of new creations.

This co-evolution within an organisation also co-evolves with the physical and social technology spaces beyond the organisation. For instance, the social technologies beyond the firm like the regulatory frameworks, the incentives in the economy to innovate, or the tolerance of failure or uncertainty will influence the physical and social technologies available within the firm.

In the same way, the physical technologies beyond the firm, like the infrastructure, access to scarce equipment or expertise or access to required inputs will also shape the choices of physical and social technologies available to the leadership.

The point is that the social and physical technologies harnessed in any organisation is not isolated from the social and physical technologies in the environment around the firm. Ideas cross over the permeable boundaries of the organisation.

Of course, we expect innovative leaders to create internal environments that are much more conducive than external environments around their firms. However, we know how hard it is to get this right. In many developing countries, leaders of companies (but also government departments) have to contend with a wide range of challenges that make the deployment of more recent physical and social technologies very hard – largely because of a lack of diversity and depth in the social and physical technologies beyond their organisation. I will come back to this in a moment.

In 2006, Eric Beinhocker published The Origin of Wealth: Evolution, Complexity, and the Radical Remaking of Economics. It is one of the books that have influenced my thinking the most. In his book, Beinhocker reframes the social and physical spaces introduced by Nelson and Winter as “design spaces” within which entrepreneurs and leaders have to make choices based on their resources, their capabilities, the external environment and the markets they are in.

Beinhocker also introduces a third design space that he calls the Business Plan design space. This is where entrepreneurs, leaders and innovators have to meld physical and social technologies together under a strategy, and then create routines that express the resulting design into the economic world. This strategy must include ways to raise finance, attract talent, set priorities, allocate resources and create an internal environment that is typically distinct from the external environment. From my experience of working with innovative teams, I know that this business plan space could also be described as an “entrepreneurial technology” because. Just like the other two design spaces, entrepreneurial technologies are created by combining knowledge modules, insights, talent, networks and competencies into new configurations.

So now we have three design spaces that co-evolve in a given organisation. There are physical technologies, social technologies and business plans/entrepreneurial technologies. At the same time, this co-evolution in the organisation also co-evolves with the design spaces beyond the firm. The inside of the organisation exchanges genetic material with the design spaces in the immediate and even more distant design spaces.

To tie this back to the evolutionary algorithm, within each of these three design spaces, variety is created, selections are made, and “good” ideas are amplified. A “good” idea meets the requirements of the internal idea markets within organisations and eventually must also meet the fitness criteria in the marketplace.

Innovation is not only about designing better physical technologies, we also need to foster innovation in the other design spaces within and beyond firms. It is very hard (I would go as far as claiming it is impossible) to successfully innovate in one design space without affecting the innovation potential in the other design spaces.

At the same time, development practitioners must pay attention to how the design spaces within organisations affect or interact with the design spaces beyond firms. This is where the co-evolution of companies, public organisations, universities and other social organisations and the physical infrastructure co-evolve.

Sources:

Beinhocker, E.D. 2007.  The origin of wealth. Evolution, complexity, and the radical remaking of economics. London: Random House.

Nelson, R.R. and Winter, S.G. 1982.  An Evolutionary Theory of Economic Change. Cambridge, MA: Belknap Press of Harvard University Press.

Evolution in the economy

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.