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

Mesopartner Engagement event on Meso Resilience

On Thursday, 23 February, Mesopartner will host an event to discuss our research and exploration on the theme of Improving Meso Resilience.

The Mesopartner Engagement series is about sharing progress on our research with practitioners also innovating in a specific topic. This will not be a training event but about research, method development, practice and searching for opportunities to collaborate or learn together. 

We will briefly explain the topic to set the scene, but we will quickly move to recent developments, challenges faced, or potential ideas we can explore together.

Background to the Meso Resilience event

Our research on Meso resilience is all about helping people working within networks of organisations to improve innovation and resilience within and beyond the organisations they work for or with. In our vocabulary, a meso organisation or programme was created to address a particular “failure” or pattern of underperformance in the economy. In our experience, we know that these organisations often struggle to adjust to changes in the production structure and the broader market conditions or are challenged increasingly by changes in the use of knowledge and technology. 

When doing economic development, we often work at two levels: 

  • the level of the meso space where there are many different organisations or programmes, or
  • the level of a particular meso organisation or programme. 

Mesopartner has published extensively on the topic of meso resilience, so here are some links to publications that will help you catch up with where we are:

The Meso Resilience research area was launched to look at the relations and dynamism between different organisations in the Meso Space. For this engagement meeting, two papers are most relevant for background reading. The first is  “A resilient meso space to enable an adaptive Systemic Competitiveness landscape” and a “case study about improving the resolution of the meso layer“. 

Some of you also know about our work on The Meso Assessment Framework (before COVID). This framework was developed to assess a specific meso organisation’s ability to innovate in relation to the changing technology & market requirements of the economy or a given sector. In the last few months, there has been an increased interest in the Meso Assessment Framework, so if time permits, we can discuss that. The article that goes with this framework can be found here. An example of the framework itself can be downloaded here. 

Event Details:

Topic: Mesopartner Engagement: Meso Resilience

Time: Feb 23, 2023 09:30 AM Amsterdam, Berlin, Rome, Stockholm, Vienna

You can still register to participate here.

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.

Exploring the gaps between universities and industries

When working on technological change and the improvement of innovation systems, the topic of the different gaps between universities and industries often comes up. This is true for South Africa, but also for my work in Europe and Asia. The gaps are described differently by development projects, academics and business people, and my job is to usually figure out where the opportunity to close these gaps lies.

In my experience of trying to close some of these gaps, it is important to be as specific as possible about nature and maybe even the effects of these gaps. It is important to go to businesses and to find out what they expect from universities, while also going to academics and researchers and finding out what they expect from the industry. Often, the expectations expressed by these two groups are unreasonable and hard to reconcile. Sometimes people are simply wrong about what they think is needed or should be done.

However, these different expectations are not the biggest obstacle to closing the gap. Often the bigger obstacle is a lack of imagination of what is even possible in terms of cooperation, interaction and information flow. This is made worse by low levels of trust by one side of the other side. Also, stakeholders often have little insight into how others value certain interactions and information flows.

Over the last 14 years I have worked occasionally with a Faculty of Engineering at a University of Technology. In the image below, I share some of the different interaction patterns that we have observed over the years of closing gaps between selected departments or technology centres and industries. I am grateful to Dr SJ Jacobs who agreed that I can share this illustration.

The possible different relations between universities and industries

Of course, some relationships are more important than others. Also, not everybody agrees with the direction of the arrows that I have used in the diagram. I also know that some academics find it hard to believe that they can learn from industry. At the same time, many business people are surprised when they realise that their own companies have learned through the personal relations of their employees with their alma mater.

Even if a certain relationship adds little value in the bigger scheme of things, for the people directly involved it could mean a lot. For instance, for an engineering student to find an industry project that they could work on as a research project is a big deal, even if this may not be so important for a company or even for the academic department involved. In many post-graduate degrees, students are required to work on a real-life project, which often requires a company to give a student access to their facilities, data, senior management or other resources.

To reflect on the relations between a university and a community or a region would require another picture, but I will do that in a next project.

To be transparent, for many years I have used a simpler version of this map that was developed by the late Jorg Meyer-Stamer in the early 2000s. I include the original map below. I think many of my readers might have seen this map in RALIS (Rapid Appraisal of Local Innovation Systems) training course material or RALIS diagnostic processes.

The original map developed by Jorg Meyer-Stamer

While this original map is still useful to explain the different kinds of interactions between the private sector and a university, I found that we need a more detailed diagram if we want to improve relationships, design new services or improve the performance of programmes.

What do you use to map the relations?

What are some of the common myths or gaps that you come across often when you work on this topic?

Different kinds of technology dissemination

In many of the projects where I work, we face the challenge of gaining access to publicly funded resources that the private sector finds hard to reach. These technological resources could be in the form of scarce equipment, specialists or even in the form of codified or tacit knowledge. Often, the private sector is not even aware of the technological resources in their location or country.

I often describe three kinds of technology dissemination:

  • Technology development, which is usually project based and involves the development of very specific technological solutions
  • Technology transfer, which is usually based on a contract between the provider and the recipient that specifies pre-conditions, conditions and which equipment, processes and in some cases expertise will be transferred to the recipient
  • Technology extension, which is usually more interactive in nature. A knowledge holder, like a university department, research lab or enterprise support centre, extends their resources to private enterprises in a complementary way.

In my experience of working on the gap between public technological infrastructure and the needs of the enterprises, each of the three forms of technological dissemination works in some contexts and fall short in others.

  • Policymakers and public funders often prefer technology development because it leverages other scientific infrastructure investments at research organisations and universities. From a demand perspective, it is usually only those companies that have sufficient in-house expertise to develop a specification or that can afford to commission a research or development project with a research organisation that can benefit from this approach. I have only come across a handfull of small companies that have been able to commision technology development projects like this. In most cases, the founders of these enterprises had deep expertise in the technological domain, their internal processes, materials and the markets. I am thinking of one case where a small engineering company specilasing in advanced optics commissioned a research project to develop a new control interface for an aircraft.
  • Public bureaucrats often like technology transfer because it leverages research outputs at universities and research labs. Technology transfer requires that careful attention is paid to intellectual property and that recipients are able to absorb and leverage the technology they are gaining access to. I typically try to avoid this kind of work because I have often found that there are huge gaps between how public researchers and private investors value intelectual property. But I also know of many instances where a technology was developed in a university and then transferred to private enterprises. In my experience, there is a huge gap between what researchers in universities and public research organisations work on, and what small enterprises trying to carve out a niche in a smaller domestic market needs.

In my opinion, the importance of both technology development and technology transfer programmes is often over-rated in developing countries.

At the same time, the value of technology extension is often under-rated. Out of concerns that valuable intellectual property might leak out, many researchers, academics or other officials cannot provide assistance or advice to the private sector. While I understand this concern, in my experience, many enterprises are actually searching for somebody to point them in the right direction – they are not always asking for specific technical solutions that would infringe on intellectual property regulations.

Technology extension involves services like:

  • Demonstrating how certain (scarce) technologies work, or showing how scientific and engineering principles can be appled to real world problems
  • Advising companies on how they can improve or optimise their current processes
  • Providing technical problem solving, analytical or diagnostic services
  • Providing access to scarce equipment, software (like design or modelling software) and access to scarce expertise.

What makes technology extension more difficult is that the advice provided must fit the enterprise’s context and capability. For instance, while companies can pay to get their products tested or certified, very few companies have access to a lab or technology centre where they can get design feedback to make their product more compliant or more economical to produce. At the same time, many universities and public research organisations can provide a basic analysis and design feedback service.

A challenge for the private sector is that public research organisations are often like labyrinths. It is hard to know where the expertise, capabilities, or excellence lies in buildings or behind closed doors. Often you cannot even get into these buildings without an invitation and, in some cases, security clearance. Nevertheless, I love wandering the corridors of these organisations and seeing what technologists are working on. Often there are prototypes, half-dismantled instruments or posters adorning the corridors. The people working there can tell the most amazing stories of how they had to solve a problem, make up for a missing bit, or how they discovered that X could be substituted for Y. When I ask them who in the rest of the world knows what they are doing, I am often met with a shrug, and a “nobody is really interested in this”.

When I ask technologists, scientists and engineers in public research organisations who can most benefit from their genius, I am often told that ex-students, former colleagues and their alumni are often the most valuable customers and sources of inspiration. This seems consistent with the notion that the best form of technology transfer is through the mobility of people. It might imply that I have to introduce “technology transfer through human mobility” as a fourth kind of dissemination.

Image credit: The image at the top of this blog is from an optics lab at the National Metrology Institute of South Africa (NMISA). I took the picture while touring their facilities in March 2020, just a few days before the strict lockdown was announced in South Africa.

Series: Promoting innovation systems praxis in Africa

This year there have been several series of events celebrating the centenary of Christopher Freeman, one of the founding fathers of the study of innovation systems. The different events highlighted many older ideas that are still relevant while pondering how some new ideas might play out into the future.

These events provided the perfect opportunity to read up on many of the essential publications created in the Innovation Systems field in the last 40 years. Many of the ideas developed by these scholars have had a profound impact on my praxis. In the next few posts, I will highlight some of the insights that I have gained from this series of events.

During a recent event, the 3rd “Putting Africa First” panel discussion based on the excellent book by the same name edited by Bengt-Åke Lundvall, Mammo Muchie and Peter Gammeltoft, Prof Mammo Muchie invited me to share some thoughts from the perspective of an innovation systems practitioners.

The remainder of this post expands one of the points I shared during the event about the role of innovation systems practitioners in Africa.

There is too much focus on technological and scientific knowledge and not enough emphasis on learning and innovating in social technologies.”

I am not arguing that we invest less in strengthening scientific research in Africa. Scientific research should continue in areas where Africa face unique or pressing challenges. There are many knowledge domains where learning primarily takes place through scientific research. Examples are healthcare, water management, drought management, etc. that are very important in Africa but are not attractive to international research efforts.

However, we must admit that strengthening scientific research capacity is more exclusive; it involves fewer people, costs more, and takes longer to show results. Moreover, this kind of knowledge accumulation is driven by scientists, engineers, technologists and professional management.

Instead, we have to invest more effort into learning. As practitioners, we must mobilise industries, academics, innovators, and policymakers to learn about problems or opportunities they can explore together in their local or regional context.

In many African Innovation Systems, I believe that this kind of knowledge accumulation through learning-by-doing involves a different set of actors. The attention shifts from universities and supporting organisations towards firms and industries, where most learning-by-doing takes place. Scientists, engineers from academia and other supporting organisations can still play a valuable role here, but the emphasis is different. The mode is also different. Learning-by-doing is a social process. To be effective, it must be inclusive, transparent and accessible to a broader stakeholder network.

Whereas in science management we try to manage risk, in learning-by-doing we try to reduce the risks of trying something new, often involving somebody or knowledge from beyond the organisation.

The role of the innovation systems practitioner is also different. Our function is to enable learning, enable knowledge exchange, joint problem-solving and adaptation of institutional mandates. We often have to overcome coordination failures that constrain investment or reduce the search costs of finding technological expertise or solutions available in the system – irrespective of whether the capability resides in the public or the private sectors. We must often connect decision-makers from different spheres of society, fragmented institutions, divergent knowledge domains, and capabilities around a theme or a topic that matters to an industry.

So, for example, I often take individuals from universities or other supporting organisations to go and visit companies, factories or farms. Or I take entrepreneurs and their staff to go and visit research labs or other technical organisations.

There are two challenges that I have to overcome when I work with technology and education institutions that want to have a more meaningful impact on the innovation system:

  • Firstly, academics, engineers, and policymakers must not see the companies they want to reach as beneficiaries of their wisdom. Nor should they see companies and the technological choices they make as subjects in a research project. I have to help these institutions listen and carefully observe how companies make investment, recruitment or technological decisions.
  • Secondly, technological and educational institutions often have low credibility with or relevance to the private sector. Or worse, institutions like university research centres, research labs, and other specialised organisations may even look down on the private sector.

To get a social learning process going within a firm, or between firms, or even more importantly, between firms and their supporting institutions, I have to find something that different people have in common. In my experience, it seems like it is easier to get companies to work together on problems that are too difficult for individual companies to solve by themselves. Perhaps this is the case because it is easier to quantify the value of a potential solution. It seems much harder to build trust around an opportunity where different stakeholders are worried that others derive more benefits from the process than they are.

I received this image via a Whatsapp message and could not figure out the origins of the photo. The rabbit and the tortoise reminds me of the two modes of learning.

September update

It is spring here in Pretoria. Many of the plants and trees in our garden and our neighborhood are growing new leaves. We are all waiting for the first spring rains to wash the dust and pollens from the air.

In my work, there are also new green shoots that I want to share with my readers and my friends.

  • I have been appointed as a Professor of Practice with the DST/NRF/Newton Fund Trilateral Research Chair in Transformative Innovation, the 4th Industrial Revolution and Sustainable Development hosted by the University of Johannesburg. I am grateful to Prof Erika Kraemer-Mbula and her team for making me part of their team, even if I am only a part-time member of faculty. My role in the research chair is to make the abstract and often-academic literature more accessable to practitioners and post-graduate students here in Africa, while bringing my practical experience into the academic discourse. I will also be able to further pursue my research into the role and performance of innovation intermedaries and meso organisations with the research chair. I have already participated in several calls with post-graduate students and some of the other members of faculty.
  • As many of my regular blog readers would know, I have been contracted since 2018 to do research and policy advisory work on the topic of technological disruption with the not-for-profit research organisation called TIPS (Trade and Industry Policy Strategies). We are now using the insigths gained from our research to develop analytical and process instruments, and are already applying these frameworks in the South African plastics, metals, automotive and leather and footwear industries. It is rewarding to see how these ideas can be used in practice to gain a better understanding of how business people and supporting organisations innovate, learn about new technological possibilities and develop new capabilities.
  • My first year of serving on one of the WEFs Global Future Council for the New Agenda for Economic Growth and Recovery have come to an end, and my term was extended for another year. During the regular meetings with my fellow council members I have realised how local insights into businesses, supporting organisations and the dynamics in locations can contribute to a global perspective on economic change and collective action.

The singing of the birds outside urge me to also want to celebrate the arrival of the new season. Of course these green shoots had its origins in previous seasons, and I am thankful for this continuity that goes on even when I don’t pay attention to it often enough. I want to express my gratitude to God for the ongoing provision that we receive as a family, despite the destruction caused by the pandemic and the responses of governments to it. I am constantly reflecting on how I can be more effective in blessing others out of the abundance that we receive as a family and as a business. I know that writing blog posts and developing short text modules is one small way of encouraging others, and I want to commit again to thinking-out-loud with my friends and collaborators.

In the days to come I will share some reflections about innovation systems, competence building, learning and some of the other topics I have been working on in the last few months.

The photo at the top of this message was taken by Caitlin Cunningham in our garden just before sunset earlier this week.

Untangling digitisation, digitalisation and digital transformation

I was recently invited by the Reconomy Programme and the Helvetas working group on Market Systems Development to address practitioners working on economic development in the Balkan region. I was specifically asked to untangle the concepts of digitisation, digitalisation and digital transformation in the context of international development cooperation.

The remainder of this post are the notes that I prepared for this call.

We are increasingly using the words digitisation and digitalisation to refer to certain kinds of economic development and changes to how work is done. These words are often used incorrectly as synonyms to refer to the increased use of software and other electronic gadgetry in everyday life. Every now and then the term digital transformation is also used.

Even though these words sound and look very similar, they are different concepts that are all somehow related. Let me try to explain what these three concepts are about.

Digitisation is the process of converting analogue information into digital information. An example of digitisation is when you convert your old vinyl records to MP3 format, or when you scan your old, printed photos so that you can store them in digital format on your computer. 

Digitisation has slowly crept into our lives over the past several decades. It started with measuring changes in natural phenomena, for instance measuring speed, distance, temperature, vibration, time or altitude. Analog information was simply converted into data points represented by blinking warning lights, alarm bells and bright red digits. Slowly the focus shifted to using digital instructions to control mechanical objects. Consider how vehicle dashboards and instrument panels of aircraft have changed over the past thirty years. 

The digitising process often combines mechanical and electrical/electronic systems, in other words, it combines different knowledge and technology domains into an integrated solution.  As more diverse knowledge domains were integrated, so the reliance on processors and logical operations increased. Initially coding was limited to logic programming of chips, but over time the complexity of coding has increased as the cost and size of chips came down, while the processing power increased. 

Digitalisation is different from digitisation. It describes the use of digital technologies and digitised data to change how we get things done. For instance, emails have replaced (most) physical post, and social media is increasingly replacing phone calls. We buy and rent music from an audio library service instead of buying music CDs.

Our attention shifts from using a digital device, or manipulating digital data. Often different people can use the same digital content for different purposes. For instance, various engineering teams can simultaneously design separate components of an integrated system, such as a car or an aircraft. A the same time another team could be using software to test the performance of digital designs to ensure that they meet performance specifications before they are approved for manufacturing, while another team is working on new materials.

Digitalisation is not only about using physical technologies, data files, software and expertise. It describes the creation of new social arrangements where different people, experts or organisations can cooperate in new ways by sharing digital information. The interoperability of data between different physical technologies and social technologies is what connects digital systems and blurs the lines between traditional industries. Digitalisation makes new arrangements possible that are very difficult or expensive to accomplish in conventional ways. An everyday example of digitalisation is how a photo captured on your smartphone can be synchronised to your computer, posted to your friends via social media and combined with the photos of other people in a digital album stored on a server in another country. 

Digital transformation goes further than simply gadgets, software, geeks and data. It describes an evolutionary process where the social relations between individuals, groups, organisations and social institutions are transformed over time because of the exploitation of new capabilities afforded by digital technologies. The emphasis shifts from the application of digital technology or the exchange of data to creating new ways for people to interact and cooperate towards shared goals. Over time new norms and social institutions evolve that supersede conventional paradigms.

In digital transformation, the traditional boundaries between different knowledge or technology domains shift or disappear. Existing scientific knowledge is creatively combined with new technological capabilities that are reinforced by the emergence of new social institutions like norms or new organisations. 

***

Transformations are essential because conventional paradigms, politics and socioeconomic arrangements are interlocked and re-inforcing a robust construct that only permits incremental changes. This conventional interlocking system makes it hard for radically new ideas and arrangements to get any traction; it often takes an almost fanatic effort to get something new to start in domains where tradition, institutions and older norms have become fossilised.

Transformations often originate in niches that are off to one side where the established leaders and ideas don’t mind (too much). In these niches, an idea or a movement slowly gains momentum as it creates new routines, norms, where new arrangements or combinations can be tried and where confidence can be built.

Social media has made it possible for different niche champions to be connected internationally, even if they feel oddly disconnected from their local realities. In these (global) communities, ideas are exchanged, courage is strengthened and collaborations developed.

As I mentioned before, digital transformation is about far more than making changes to the system by adding digital front-ends, digital services or a search box. A collegue working in public sector reform told me that once communities understand that they can hold public officials and political representatives accountable, the whole initiative got a life of its own. What started off as a way to improve transparency and accountability through digitalisation, ended up being about democracy, governance, public service quality and managing public resources better. Of course, it is also much easier to design and improve public services and impact when communities are keen to be involved.

This explains why a digital transformation in a system is not only about the “digital” or the “system”, but how these interact within a broader socioeconomic context. We have to figure out which higher-order questions to ask.

Can you imagine what it would take to digitally transform a system in your economy? For instance, what would it take to digitally transform an education system in a country? Which combinations of norms, knowledge domains, governance, institutions and technologies would have to be tried to enable such a transformation? It is not possible to design this kind of system upfront. And it is not merely an IT problem. It requires many innovations in different areas such as regulations, processes, systems, organisations, subjects, management and delivery. For digital transformation some solutions would be digital, several would be political, and most would certainly be contested by those already in power.

***

The phenomena of digitisation, digitalisation and digital transformation are fuelled by faster processing, smaller components enabled by new materials, improved energy consumption and reliable and fast connectivity. 

However, digitalisation requires more than advances in hardware and coding; it also requires the integration of different systems and a re-imagination of what is possible with data. It asks of us to combine scientific knowledge with an understanding of how people can work together in new ways. Digitalisation pulls our vision to create new ways of doing things, it asks of us to let go of trying to optimise what we already have in place.

Digital transformation goes even further that digitalisation, as it requires that conventional arrangements, institutions and norms be challenged by entrepreneurs, scientists, engineers and change makers who want to use digital technologies to challenge existing dominant paradigms that are no longer effective.

***

It would be a mistake to think of digitalisation and digital transformation too narrowly from the perspective of ICT, software development or known digital solutions. Of course, it goes without saying that computer programmers, coders and ICT start-ups are still important. Yet digitalisation more often draws on a fundamental understanding of the underlying natural sciences used in a society and how these existing systems could be re-imagined in combination with digital technologies. It requires the ability to integrate systems that are now separate to achieve a specific goal. It asks us to set aside the ambition to incrementally improve different systems and re-think solutions and challenges in a more integrated and holistic way. 

Development projects can support digitalisation by helping developing countries to figure out where conventional processes and social arrangements are too cumbersome or completely lacking to encourage economic growth and investment. Development organisations should remember that the focus of digitalisation is not only on digital skills, technologies and imported solutions, but on how these are combined with other knowledge and scientific domains. Lastly, for digital transformation to occur, diverse stakeholders must work together to re-imagine new ways of doing things in areas where conventional solutions are no longer effective. This requires facilitation and a technology-neutral facilitator that can encourage local stakeholders to experiment with new solutions that combine existing knowledge in new combinations with digital technologies. 

Both digitalisation and digital transformation take much longer to accomplish than a typical development project, and both often need to be nurtured despite resistance from the established interest groups affected by the emergence of a different paradigm. It may be necessary to assist the stakeholders to develop action plans that show results both in the short as well as the long term, otherwise some stakeholders might run out of energy before sufficient gains have been made. 

Lastly, transformations are evolutionary processes. It is not possible to design the ideal end-state and then develop a plan of how to get there. The path from the present to the future is not straight or easy to plan. At best we may be able to figure out a few steps or concurrent processes.

Transformations often start with dissatisfaction with the status quo and a desire to cause a variation of the current trajectory. Or it can sometimes be sparked by a crazy idea starting with “what if we tried this instead?” Often the initiators of transformations are quite naïve about what it would take to see the transformations through. We must therefore step up beside them and help them to build their case for change, to encourage them when they face resistance or when experiments don’t work, and to help them balance the short-term and the longer-term priorities. 

Further reading.

I have benefitted immensely from the publications by Frank Geels and Johan Schot, to name two authors. Searching for deep transitions, socio-technical change or multi-level change will also yield great results.

If there is sufficient interest I can also write a follow-up article about some of the literature that I have found most relevant.

Image by Gerd Altmann from Pixabay

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