Some of the challenge prospective clients that reach out to me are grappling with

Due to my research, public speaking and writing my favourite topics I regularly receive requests to help somebody that is grappling with an issue either around meso-organisational change or about technological capability, innovation or disruption.

Usually after a few emails we schedule a phone call to discuss their context, their intent and my service offering. Thanks to my journal and reflection processes I can track the original requests and the ensuing correspondence or projects. Over the last six months, I have noticed some patterns that are now repeating. Here are some of the most frequently discussed points. While I can help with some of these, with some I cannot help for various reasons.

Because I have always focused on training other consultants and my own clients, I thought it would be a good idea to share these early observations with you.  (Larry, Goran, Bojan, Nik, Albina, Garth, these are for you). To save you all from many emails, I have written 8 blog posts in one!

So here are the emerging patterns of 2019:

  1. I am frequently contacted by organisations or projects that believe that technological change, or preparing for the 4th industrial revolution (4IR) is a project. That there is something that we can do quickly (one of the most popular search terms on this blogsite is “formula for 4IR” and “4IR method”. Preparing for technological change, responding to disruptions, or even preparing to disrupt others is a capability that is distributed over companies, public and civil organisations, regions and individuals and over time. It is not a project that ends, it is a capability that must be continuously nurtured. After addressing one threat or challenge and the next two will be on the horizon. While I love training, what these organisations really need are new technology, innovation, change and knowledge management capabilities.
  2. I am asked by development organisations to prepare their target groups or beneficiaries for the 4th industrial revolution by focusing on one threat. For instance by mastering computer-aided design, design thinking, or helping entrepreneur to cope with advances in digitalisation, 3D printing, or master some automation or sensor technologies. However, the reason why so many people lump so many technological advances together under the banner of the 4th industrial revolution is that these technologies are converging, and if they are not yet converging, they are rapidly learning from each other. That means the capabilities are converging or starting to follow similar evolutionary patterns.  That also means that very few economic activities are left untouched by changes in other sectors, technologies and markets. Again, this is not about training. It is about competence, leadership, sense-making and innovation. Perhaps it is mostly about learning, relearning and knowing what you have to master next. People also commonly confuse “digitalisation” with writing software, whilst telecommunication costs, insufficient regulatory frameworks for e-commerce, closed government (as opposed to open government) or very fast connectivity and data security are ignored.
    People that can quickly master a new domain, like machine learning, big data or concurrent design, will have a distinct advantage in the future. People that are specialised in one skill, especially a vocational skill, may be more vulnerable. But my main point here is that splitting up the technologies is not helpful. Again, the broad technical capability must be fostered. However, in addition to point 1, I want to add that the ability to track, master, integrate and leverage multiple specialised domains continuously over time is very important, even if they do not yet appear to have a relation to your industry, business or organisation.
  3. I am asked to help only the private sector in a country, region or sector. Many organisations believe that the private sector is most vulnerable to disruptions. I believe that many competent firms would be OK, but not all. Uncompetitive companies, un-innovative companies and undermanaged companies are going to be more vulnerable unless the state can afford to protect them and in so doing possibly raising the costs to the society. But what we must not lose focus of is that when one public sector organisation, programme or function fails, the effects could be far-reaching. Take for instance what happens when a local municipality in a developing country is undermanaged. It will affect the whole community. The challenge is that in developing countries the “revolution” or the “disruption” will be about social institutions (local government, universities, technical vocation colleges, schools, or whole governments etc.) that will be caught in a weak position – and unable to catch up or get ahead. So supporting the private sector in a place where many public institutions are failing is just naive. You do not address a market failure by focusing mainly on the private sector, just as you do not address government failure by only working with the government. 
  4. This point is an extension of the previous point. Many organisations that approach me want me to help them get the private sector more innovative. But here is the problem. It is not possible to develop a prosperous and successful private sector without the same happening in the public sector and in civil society. Actually, any form of innovation starts with a good basic and often some good higher qualifications. The changes that people can work together in a sophisticated way, without these arrangements being replicated in other sectors are naive. Complex forms of cooperation within an organisation, company, NGO, school or church depends on the ability to work together to solve problems that span over the ability of individuals. This needs trust, and it comes from the broader society and its formal and informal institutions. You cannot develop the private sector in a vacuum. Management teams of companies are not suddenly going to behave in novel arrangements that don’t exist in schools, sports teams, civil organisations, universities or political parties. Maybe it is possible to develop only the private sector in the short term, but for long term economic development, healthy public sector organisations are a pre-condition. The social technologies that enable the private sector to innovate, to combine old and new ideas, to figure out new ways of arranging teams around objectives, problems and opportunities are in most countries developed with the direct or indirect help of the public sector. Often these ideas are first developed around social, political or local problems. The quickest way to instigate innovation is to focus on creativity, better decision-making and increased performance in publicly funded programmes and civil organisations. Do you want to quickly get new forms of dialogue or new technology to spread in a location? Start with the schools, the local theatre, church or community organisation – and watch how fast the private (and hopefully public) sectors will catch on. Often the most adaptive private sector leaders are serving on the boards of the schools, local NGOs, and they take up new ideas very quickly.
  5. I am often asked to assist struggling industries in developing countries to become innovative, competitive or successful. Maybe the companies were successful once, hopefully not too long ago. The challenge with sectoral upgrading is that the prominent companies must either be very competent in market development, or they must have mastery in a technological domain that has a long cycle time still ahead. With one of these two domains mastered product and process innovation is possible, but perhaps not easy. The real challenge is often that in developing countries the business model innovations are the hardest and the cost of failure are also very high. Thus the incentives to try new business arrangements are low. If the companies are not able or willing to rethink or change their business models, then there is very little one can do. The entrepreneurs that will be successful in five years from now have already made decisions to master emerging markets and technologies today, and they have found a way to foster their competence in these domains within their current companies. They have innovated in the business arrangements, enabling them to innovate in products and processes. If there are no companies that are able to do this it is most likely the best idea to rather invest public funds into investment promotion, education, tech transfer and incubation to try and offset the job-losses when the current companies fail.
  6. I am often approached by internationally funded development projects to do something to create employment in a sector or a region in a developing country. The challenge is the sectors, supporting institutions and even the approach (the ideology) is already decided and cannot be changed. Often even a quick analysis and a few phone calls reveal that the development project has read the situation wrong, or they ignored strong messages of resistance because they believe in their ideology. Yet they persist, and now they are not getting the response from the stakeholders. I notice many of TVET and green economy projects that fall in this category. Even if there is great value in what these organisations have to offer, if they are not responding the binding constraints or challenges (the decision points) faced by the entrepreneurs and government officials, their offer will not be taken up. Or it may be taken up but it won’t stick. My approach for the last few years has been to wait for the projects to realise that they will never reach their targets and then to propose that we try some alternatives to see if we can get some impact. Or I simply turn down the request. Development programmes in the education sector are often
  7. I am often asked to help manufacturers or development organisations in developing countries to prepare for technological disruption at the technological frontier. That means technologies that are newly emerging. The problem is, most companies in developing countries will not be disrupted by cutting edge technology. They will be disrupted when older technologies reach new levels of efficiency and scale, perhaps in combination with newer technology. That means that an older technology evolves to become available as a utility service or on a pay-per-use basis. That is how the fundamental disruptions occur that completely displaces existing markets and sociotechnical arrangements. An example if PV electricity to homes. In many developing countries a homeowner can now buy panels, inverters, brackets and batteries from hardware retailers (or online). It may be illegal in many countries, but homeowners can take their homes off the grid. If enough homeowners do that, national power utilities may collapse. Perhaps another example is that as developing countries switch to fibre internet connectivity, all the IT companies that used to provide small servers, desktop maintenance, server maintenance, cabling installations, etc are disappearing. They are disappearing because they have not long ago mastered an older technology (shared server-based computing, remote network maintenance) that has recently become a utility-based service.
  8. I am asked by an international development organisation to help with a project aiming to support 25, or 50 women, girls, lecturers, youth or a handful of companies. 25 out of a population of thousands or millions is really depressing. This is not systemic, nor is it sustainable. I cannot get involved in these projects, my conscience will not allow me. If any beneficiary group is so marginalised or excluded that 10, 20, or 50 seems like a good indicator of impact, then we should really be going back to the drawing board about the complexity of the system and our sensitivity to the decision points, the attractors and the boundaries in the system. Most likely we should be targeting changes in mandates, roles and functions of institutions and not be focused on individual beneficiaries. The system must be very dysfunctional (meaning somebody must be benefitting enough to keep it in this state), and focusing on getting a handful of people through the system despite all the resistance or challenges is not systemic. In fact, everybody that is inspired by this handful might suffer severe challenges to follow in their footsteps. In a complex system, fixing a little part and then scaling it up does not change the fundamental working of the system. But let me stop venting now, I am asked frequently enough to talk about the potential of complexity thinking applied to developed. Maybe this deserves a blog post of its own.

These are just some thoughts about the challenges that some organisations are grappling with when they reach out to me. These are some of the common objections that many clients are challenged by based on my writing, teaching or speaking. Perhaps these are also the reasons why some clients decide to appoint somebody else or to never reach out to me in the first place. But these are also the points that keep me awake at night, the recurring themes that come up even when I am trying to walk the dog.

Let me know if any you’ve also had these conversations, or whether your organisation, funder or clients are stuck on the same issues. If there is sufficient interest in any of these points then we can perhaps think of how to explore these deeper, or perhaps we can even get together to brainstorm these.

The evolution of technologies, industries and regions

In the earlier research on technological evolution in the 1970-1995 period, attention was mainly paid to either a whole economy or a single sector or technological paradigm. It is broadly understood from this research that different industries and technologies evolve at different rates. This means that over time, some industries may be more important than others, or at least, some may be accelerating while others may be stagnant or declining. In recent research by Saviotti and Pyka (2013), the emergence of new technologies and industries (and the goods and services that they provide) is seen as offsetting the diminishing returns that are innate in the development of existing technologies. Nelson (2015) argues that this is a reason why absorption and further development of these technologies are necessary to maintain economic development.

In enabling technological evolution in countries, a whole range of actors play a part. Individuals and informal networks, to large and small firms all play a role. However, for the last century, most technological advancements have been supported by scientists, the academia and professional societies and a range of supporting meso organisations. In Europe, professional associations often play an important role in the deepening and dissemination of technological knowledge.

I want to come back to the meso organisations mentioned in the earlier paragraph. Meso organisations or functions are created in response to structural issues like market failures, sometimes government failures or persistent patterns of underperformance in the economy. These meso functions are critical in supporting economic actors to discover what is possible in a given economic context, to assist stakeholders to overcome coordination failures, and to provide critical public goods (such as scarce or expensive technological infrastructure, demonstration facilities, testing facilities, public research, and so on).

The meso functions enable a society, industry or even the public sector to discover and absorb new ideas, they enable learning by doing, they encourage the adaptation and dissemination of new knowledge or technologies, and they connect different stakeholders to overcome coordination and search failures. These meso functions are a critical ingredient in the local innovation system as they extend the technological capability of a given sector, industry, market or region in a country.

You would have noticed that I have not yet mentioned universities and public research efforts. This is simply because I have written about them so often as they form a critical part of the local innovation system. I sometimes even think that the higher education sector receives too much attention. Yet, education from basic schooling to higher education plays a critical role. For me, a university is an important meso organisation, and research centres, technology extension centres and laboratories that provides testing facilities are all important meso functions or maybe even meso organisations hosted by a larger organisation.

The importance of the higher education sector in the technological infrastructure varies for different parts of the economy. Nelson contends that scientific and technological research and teaching, especially the more applied fields, provide a base of knowledge that is accessible to all technically sophisticated individuals and firms working to advance technology in a field (Nelson, 2015). However, different fields also depend, to different extents, on scientific and formal research and technology support. Therefore, measuring journal articles and research outputs as a contribution to the national innovation system or as a proxy for technological capability will always paint only a partial picture. It really also depends on the pace of change and scientific advancement that is taking place in a region, a technological domain or an industry.

Furthermore, different industries depend, to different extents, on government support and incentives. In some fields public support is crucial, and in other cases, provides little incentive or value. In many cases innovations preceded science, and continued development is only possible due to the iteration between researchers and enterprises. Nelson continues that the kinds of firms that do most of the innovating differ – in some fields this tends to be large, established firms while in others it is smaller firms or new start-ups (Nelson, 2015).

Nelson draws an important conclusion that has really shaped my own thinking. Nelson states that there is no single set of policies that are applicable to all technologies and industries. What will be effective in some fields will not be in others. For instance, small business promotion in some sectors in one country could work, but it could be ineffective in another country.

In South Africa, with its very high coordination costs and high compliance costs, smaller enterprises in the manufacturing sector are at a huge disadvantage. The distance to sophisticated buyers and the challenges with exports compounds the difficulty for smaller enterprises to compete globally from the local base.

Nelson is also known for his writing on the importance of a wide range of social institutions, both formal (for example a cluster development organisation) and informal (the trust networks between members of the clusters). He refers to these social institutions as social technologies, and he argues that they co-evolve with physical technologies to enable economic development. These social institutions range from central banks to a diverse range of firms, but importantly include other forms of organisations such as scientific and technological societies, universities, government agencies and even capital markets. These institutions are the focus of the discipline of innovation systems.

Nelson emphasises that “that when a potentially new technology emerges, new institutions often are needed to develop it, and invest in and operate effectively the economic practices based on it”.

Nelson acknowledges it is not an easy task, as it is hard to predict which emerging fields of promising new technologies are going to be important in driving economic progress in the future, and which will have a modest impact. The policies to create or reform institutions need to be adaptive and flexible. Arthur (2009:186) confirms the view of Nelson and argues that “We cannot tell in advance which phenomena will be discovered and converted into the basis of new technologies. Nor can we predict which combinations will be created.”

That brings me back to my intent with this post. When we look at technological disruption and change, it is very easy to get caught up in the potential or risks of any given technology. But we must not take our eye of the informal and formal institutions, market systems, regulations and technological domain specific organisations that are needed to make a new technology viable. At the same time, we also have to figure out how to gracefully exit older technologies and how to either shut down or transform public organisations that once had a critical role in supporting those industries and technologies.

Again, I repeat, the so-called fourth industrial revolution is going to be more disruptive at the level of institutions and social arrangements than it will be disruptive for the enterprises that are competing at the technological frontier.

In South Africa, we have a triple-challenge.

1 – Our institutions change very slowly, and we have huge social tensions about how to allocate resources and wealth in the economy. Our local municipalities and local economic development activities are ineffective (with some exceptions in some of the larger metros). Yet, local authorities have hardly any influence over the quality and effectiveness of national meso programmes that are supposed to enable economic change.

2 – This is compounded by a largely uncompetitive economy with lots of market concentration.  The regulatory burden in the economy keeps a lot of potential entrepreneurs employed in the corporate and the public sectors.

3 – Our discussions in South Africa about technological change, technological capability and the promotion of the innovation system is dominated by a linear logic of science leading to technology leading to innovation (the so-called STI approach). There is not enough attention being paid to the eco-system of organisations, technology extension agencies that can help enterprises master new technological domains, reduce coordination costs, the so-called Do, Use, Integrate (DUI) kind of innovation. On that point, we also have very few (if any) technological organisations tasked with transforming or upgrading whole sectors or regions in the country from a technological perspective. Everything is aimed at one enterprise at a time.

My research agenda:

This is what my research is about at the moment. I am working with a team from TIPS and the dti (South African Department of Trade and Industry) to strengthen the visibility of this technological meso network, while also strengthening the public sectors ability to spot technological disruptions and to be more pro-active.

Please sign up below if you want to stay informed of our progress as I will not be able to share all of our learning in the public space all the time.



Sources:

Arthur, W.B. 2009.  The nature of technology : what it is and how it evolves. New York: Free Press.

Nelson, R.R. 2015.  Understanding long-run economic development as an evolutionary process. Economia Politica,Vol. 32(1) pp. 11-29.

Saviotti, P.P. and Pyka, A. 2013.  The co-evolution of innovation, demand and growth. Economics of Innovation & New Technology, Vol. 225 pp. 461-482.

Technological change cycles

This is the 3rd post that draws from the research and advisory work I am currently busy with to strengthen South Africa’s technological capability to detect and better respond to discontinuous technological change. The citation information for this post is at the bottom of this post, and a link to the research report that I have copied this from is here.

During the 1980s several scholars[1] recognised that technological change follows a cyclical pattern and several models were put forward to explain the phenomena. These models are still in use today and have been found to be active at different levels of technological change. The broad consensus was that a technological change cycle:

  1. Starts with a technological discontinuity or disruption, followed by a period of unstructured and often chaotic innovation when a new idea or concept is made possible (based on preceding developments). This disruption results in a fluid or turbulent development phase during which many ideas are developed, tried and promoted as the next best thing,
  2. That is followed by an era of ferment from which a dominant design emerges; and
  3. This is followed by an era of incremental change during which the dominant design is elaborated.

This can be illustrated with the widely recognised Abernathy and Utterback (1978) model with its three phases of change that are illustrated in Figure 2. The three phases are a fluid phase, a transitional phase, and a specific phase, and is similar to the cyclical pattern described in the bullet list above. Other scholars used slightly different labels, but the characteristics in the different phases are all more or less the same.

Abernathy and Utterback

Figure 2: The Abernathy-Utterback model of technological change

Source: Abernathy and Utterback (1978)

The rate of innovation is highest during the fluid phase, during which a great deal of experimentation with product features and operational characteristics takes place between different competitors[2]. Because of all the changes in the product composition and characteristics, process innovation typically lags. Buyers and users are often confused or overwhelmed during this phase fearing that the benefits are overstated and that the costs of adaptation are uncertain. Only the brave and the innovative engage in finding, adapting and integrating new ideas and concepts.

In the transitional phase, the rate of product innovation slows down and the rate of process innovation increases. At this point, product variety gives way to standard designs that have either proven themselves in the market, or that are shaped by regulations, standards or legal constraints. The pace of innovation of how to produce the product increases. What was done earlier by highly skilled technicians may become automated or developed to a point when low-skilled operators can take over. Or lower-skills jobs are displaced from the production process to other functions like logistics, while the skills intensity on the production line is enhanced. At this point it is easier for bystanders and followers to engage in exploration. The early adopters are already over the horizon, while many early adopters have exited, sold out or moved on.

The final phase, the specific phase, is when the rate of major innovation dwindles for both product and process innovation. In this phase, the focus is on cost, volume, and capacity. Most innovations are very small incremental steps, improvements on what is already known and accepted. Latecomers can now engage with the technology, although it might already be too late.

The description of technological change provided above follows the generic three-step process of technology evolution: a process of variety creation, selection, and then amplification or retention.

  • During the variety creation phase there are many competing designs and no dominant logic. Towards the end of this phase a few dominant designs may emerge, but there is still much competition between ideas. This is not only a technical selection process, there are important social, political and industrial adjustments taking place at the same time.
  • During the selection phase, standards emerge for positively selected ideas, with a few designs dominating. It is a relatively stable process of incremental improvements in features, performance and results. This may be interrupted occasionally by leaps in performance as some designs are substituted by better technologies, or from breakthroughs often coming from other industries or contexts. In general, designs become simpler as a learning process unfolds about how best to design, manufacture, distribute and use a particular technology around dominant designs. This period is characterised by growing interdependence as modules are developed, substituted and standardised. There is a growing exchange and increased competence within and between different communities of practitioners. Often there is industry consolidation during this phase. It is important to note the dominant designs are only visible in retrospect. They reduce variation, and in turn, uncertainty, but within the process it is hard to predict which designs will survive the next set of radical innovations. Once a design becomes an industry standard it becomes hard to dislodge.
  • This leads to an amplification phase, in which the best ideas are not necessarily used as intended, but when technological changes spill over into areas not originally intended. This is a relatively stable process that can continue for long periods, until is it suddenly interrupted by a radically different idea, resulting in the process starting all over again.

Anderson and Tushman (1990) state that, from the perspective of the sociology of technology, technological change can be modelled as evolving through long periods of incremental change punctuated by revolutionary breakthroughs[3]. The innovation activities that take place that lead to these phenomena will be discussed in Chapter 3.

Arthur (2009:163) contends that change within technological domains is a slow process. He explains technology domains do not develop like individual technologies like a jet engine: focused, concentrated and rational. It is rather more like the development of legal codes: slow, organic and cumulative. With technology domains, what comes into being is not a new device or method, but a new vocabulary for expression, similar to a new language for creating and combining new functionalities.

A current example is the “Internet of things”, where the connectivity of physical devices are spreading from the office and smartphone devices to interconnect household appliances, industrial applications and an endless list of technologies enabling data exchange, control and new functionalities . It could be argued that this is not a new technology, digital sensors have been around for a long time, our cars, smartphones and equipment have contained them for a long time. However, the language, standards, distributed nature of processing, and developments in big data visualisation have all contributed to this technology appearing to arise from obscurity into the limelight of the popular media. A similar argument could be made for artificial intelligence, drone technology and others.

Notes:

[1] The work of Tushman and Anderson (1986), Abernathy and Utterback (1978) are still frequently cited today.

[2] Kuhn (1962) noted that in the early stages of research in a given field, the most that scholars typically can do is to report the phenomena they observe, without a unifying theory or framework to help them categorise or make sense of what they see. As a result, this stage of knowledge accumulation is characterised by confusion and contradiction. Theories are put forward but reports of deviating phenomena accumulate.

[3] This is often referred to as punctuated equilibrium by political scientists.

 

Sources

Abernathy, W.J. and Utterback, J.M. 1978.  Patterns of Industrial Innovation. Technology Review, Vol. 80No. 7 (June/July 1978) pp. 40-47.

Anderson, P. and Tushman, M.L. 1990.  Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change. Administrative Science Quarterly, Vol. 35No. 4 (Dec 1990) pp. 604-633.

Arthur, W.B. 2009.  The nature of technology : what it is and how it evolves. New York: Free Press.

Kuhn, T.S. 1962.  The Structure of Scientific Revolutions. Chicago & London: University of Chicago Press.

Tushman, M.L. and Anderson, P. 1986.  Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, Vol. 31No. 3 pp. 439-465.

 

Citation for this text:

(TIPS, 2018:12-13)

TIPS. 2018. Framing the concepts that underpin discontinuous technological change, technological capability and absorptive capacity. Eds, Levin, Saul and Cunningham, Shawn.  1/4, Pretoria: Trade and Industry Policy Strategy (TIPS) and behalf of the Department of Trade and Industry, South Africa.   www.tips.org.za DOWNLOAD

 

 

Exploring individual Social Technoliges that enables Systemic Change

My exploration of complexity thinking and how it enables leaders and collectives to make better decisions is taking me back to where I started. I started in organisational development and innovation. Then I shifted into larger economic systems like innovation systems, local economies, value chains or regions. For the last four years I have been working mainly on organisational development in meso organisations involved in technology development and innovation promotion. So I have come full circle, but I sense that I am now better able to synthesize and use my experience and ideas. Now I will focus on the role of individuals in changing economic systems.

Marcus Jenal and I wrote last year about Systemic Change. In our reading the wealth of literature on economic evolution we were were deeply impressed  by the work of Eric Beinhocker. In particular, the idea that economic development demands a co-evolution of:

  • Physical technologies – are methods and processes for transforming matter, energy and information from one state into another in pursuit of a goal or goals; they enable people to create products and services that are worth trading. A physical technology is not only the physical object itself, but both the design of the thing and the instructions and techniques to make and use it. The ability to learn how to use, make and adapt the physical objects is critical.
  • Social technologies – are methods, designs and arrangements for organising people in pursuit of a goal or goals; they smooth the way for cooperation and trading products and services. For example, the ability to organise people into hierarchies, such as companies or other organisations, which can allocate resources to specialised functions and which can learn is a social technology.
  • Business plans – are developed by enterprises and other organisations that are competing for resources, acceptance and buy-in in the economy. Business plans play the critical role of melding physical and social technologies together under a strategy and then operationally expressing the resulting design in the real world. From an evolutionary perspective, the purpose of business plans is to discover what is profitable, efficient or even possible in a given economic context. You could call this an economic technology.

I realized last week that I have spent at least five years of my career immersed in each of these three co-evolutions, but with the others not completely forgotten. From a physical technology perspective, I have always been involved in promoting trans disciplinary research, promoting innovation systems and helping innovators become more effective. I have spent a number of years supporting entrepreneurship, developing supply chains and promoting value chains. From a social technology perspective I have been working on management education, business consulting, assisting with change processes and facilitating search and discovery process within and between organisations.

Now I am taking this to a next level. I will for the next few months focus intentionally on the role of individual leaders in the co-evolutionary process. The co-evolution is fractal. I started at the highest level, the level of open systems, innovation systems, local economies and industries. Then I shifted to meso organisations, development organisations and universities, where I often focused on teams and how they use their resources in a systemic way to improve the networks they form part of.

The focus on individuals will be formal this time, where in the past this was informal, almost a by-product of my process consulting and advisory work. To equip me for this role I had to refresh my organisational and coaching skills. I have also participated in an advanced coaching programme in order to facilitate this shift in focus. Lastly, to enable this process I have exited many contracts, or not renewed contracts as they came to a close. This will enable me to dive deep. I will focus my coaching praxis on leadership support, innovation support and institution building, but with the role of the starting point. This will require many new business practices, and many new clients. I will try my best to frequently reflect here on my learning.

Economic complexity, the Product Space and structural change

For the last few years I have been playing with and actively following the developments around the Product Space methodology and logic. It is such a powerful instrument that I use often to support my clients, but also as I try to make sense of technological change around the world. I am grateful for Ricardo Hausmann and Cesar Hidalgo and their teams in responding to my many questions, and their patience when I tried to figure out how to get my own product space server going.

Here is an image of the complete Product Space map from the Atlas of Economic Complexity page (you can also download the book from here). The image below shows where different industries are on the map. I work mainly in the blues, purples and some other colors I can cannot name on the left half of this map.

 

Beyond the great visual interfaces and interactive tools that the Harvard CID and MIT Media Labs offer, there is a great depth of knowledge and insights about how economies change. Take a look at this quote in a summary by Hidalgo and Hartmann on the OECD Insight page (the link to the main article is at the bottom of the OECD page)

“Scholars have argued that income inequality depends on a variety of factors, from an economy’s factor endowments, geography, and institutions, to its historical trajectories, changes in technology, and returns to capital. The combination of these factors should be expressed in the mix of products that a country makes. For example, colonial economies that specialised in a narrow set of agricultural or mineral products tend to have more unequal distributions of political power, human capital, and wealth. Conversely, sophisticated products, like medical imaging devices or electronic components, are typically produced in diversified economies that require more inclusive institutions. Complex industries and complex economies thrive when workers are able to contribute their creative input to the activities of firms.”

As I mainly support developing countries, this paragraph is really important to me. Perhaps this explains why I have become increasingly cynical of much of economic development practice. I find that in developing countries the governments but also international development often concentrate on value chains or sub sector support activities or private sector development strategies that focus exactly on the wrong parts of the economic system. These sectors are at the edges of the product space, with very low skill requirements and with little technology spill overs from these sectors to other parts of the economy. This focus is largely because of a belief that jobs can be created easily in these sectors (in the shorter term), instead of focusing on areas of the economy where economic complexity can be strengthened (in the longer term). It saddens me to hear of another development project, focusing “directly” on a group of firms, farmers or beneficiaries, in order to create jobs. This will not help in the longer term, even if may help in the shorter term. Often the reason offered for bypassing local stakeholders, government programs, etc are that they are “part of the problem” or “too slow”. No wonder the inequality is rising and growth is slow.

Economic complexity is a measure of the knowledge in a society that gets translated into the products it makes. The most complex products are sophisticated chemicals and machinery, whereas the least complex products are raw materials or simple agricultural products. The economic complexity of a country depends on the complexity of the products it exports. A country is considered complex if it exports not only highly complex products but also a large number of different products. To calculate the economic complexity of a country, we measure the average ubiquity of the products it exports, then the average diversity of the countries that make those products, and so forth.

To change the productive structure of an economy will take both public and private focus on building the right kinds of institutions, both formal in the sense of organizations, policies, etc. and informal institutions, in terms of trust, cooperative capability and maybe even cultural change. On a few occasions I have been accused that my focus on knowledge intensification, innovation systems and complexity only benefits the “have’s” and excludes the “have nots”.  To work with institutional or structural change you will almost certainly work with wealthier, or more powerful counterparts. Like the management of an university department, senior government officials or an entrepreneur that is trying new combinations.  My argument is that this accusation confuses target groups (those that we can work with to enable a change) with beneficiaries (those that will ultimately benefit from change). Furthermore, if we have to work with academics, scientists or pioneering entrepreneurs, we must certainly set conditions that ensure that benefits are inclusive and not exclusive. It means that the focus in development needs to shift on purpose towards enabling more responsive and forward looking institutions, institutions that lowers the costs for entrepreneurs to try new combinations, institutions that equip employees to find opportunities to contribute their knowledge, skills and creativity towards more complex and valuable economic activities.

Marcus Jenal and I have tried to contribute to this discussion with our paper about Systemic Change that was published at the end of last year. For more information, see this post on our Systemic Insight page. This is the site where we write about our thinking into how complexity thinking can be used to improve development.

Sources:

HIDALGO, C.A., HARTMANN, D., 2016 Economic complexity, institutions, and income inequality, OECD Insights, http://www.oecd-ilibrary.org/economics/debate-the-issues-complexity-and-policy-making_9789264271531-e

HARTMANN, D., GUEVARA, M., JARA-FIGUEROA, C., ARISTARÁN, M. & HIDALGO, C.A. 2015. Linking Economic Complexity, Institutions and Income Inequality.

 

Unlocking knowledge in organisations

A favorite topic that I love to talk, think and write about is the knowledge that is lurking around in organisations, often untapped.

Last week, the University of Stellenbosch Business School, where I am a member of faculty in the Executive Development programme, published an article I wrote in its thought leader newsletter. It is titled “Unlocking knowledge in organisations to enable innovation”. What started off as a 1200 word article was reduced to 700 words by Linton Davies, the wordsmith that always helps me to better express my ideas when I write formal publications. I think this article as it stands now must be the most I have ever said in only 700 words!

I am really proud of this article in its current short form. It started off many years ago as a much a more complicated module in my innovation systems training session. Now it is a practical workshop format that I use often in organisations supporting innovation, but increasingly in businesses, government programmes and even NGOs.

It is informed by evolutionary and complexity thinking, and is thus in line with my current research and the principles that I now pursue and value. Of course, a lot of extremely important theory is left out in this form, but by helping managers become more aware of how the inhibit or promote knowledge generation in their organisations is for me already a great start.

 

Systemic Insight – Economic development is about introducing options, not bringing solutions

Marcus and I have just posted a new article on the Systemic Insight website. The post is about our recent article that was published in the IDS Bulletin (Vol 46.3) and is titled “Explore, Scale Up, Move Out: Three Phases to Managing Change under Conditions of Uncertainty”. 

Please note that in future all my posts specifically about complexity and resilience will be published on our Systemic Insight website. To my regular blog readers it may be worthwhile to also subscribe to the feed on that site. We promise to write more often now that the foundation for our applied research theme on complexity in development has been created. We already have many customers using our approaches and this area of work is promising and rewarding. We have added a new page to the Systemic Insight site that explains some of our most frequently asked about services related to complexity thinking applied to development.

On this site I will keep on writing about Private Sector Development in general, and particularly on innovation and innovation systems.

Your feedback, comments, emails, phone calls, tweets and likes are appreciated. Let us know what you think and what you would like to discuss, read about or just “air”.

Best wishes,

Shawn

The oblique search for new industrial opportunities

Industrial policy is typically set at national level. It is often aspirational and attempting to “stretch” an economy into new kinds of production and value addition. Programmes are designed, targets are set such as doubling manufacturing contribution of x% within 7 years. Therefore it is sometimes disconnected from the present as it seeks a new Status Quo, a different structure of production.

Yet the natural process under which new production activities are created is complex. It is not as simple as finding a market opportunity, finding the right production process, securing funding and launching a business. The economic context, the political climate, the entrepreneurs with the right levels of experience, backing and confidence are all needed. And don’t forget individuals with a desire to expand, take risks and try new things.

Danni Rodrik argues that Industrial Policy should be a search and learning process. Many centrally planned industrial policies even cite Rodrik as they then commence with outlining with great certainty what must be done, by whom, with which resources and to which effect. This logic completely ignores the importance of what exists, and what is possible from here. It ignores that fact that the past matters, and that the current structures are the result of a series of evolutionary steps. Complexity science teach us that these plans ignore the fitness landscape, a landscape that is dynamic and constantly changing. Any attempt to extend the horison further than what is within reach should be treated with great caution. One of the greatest obstacles is the attide towards risk and the optimism of enterprises. I don’t think Rodrik meant the ministers officials must do the search, rather, industry must do the search or at least be actively involved in the search in partnership with government and institutions.

But the search is not about answering a simple question. A more oblique approach is called for (see John Kay, Obliquity). Which means we should set aside targets and indicators, and focus on creating small experiments to introduce more variety and options into the system. It means that finding out that something is not possible is as valueble as figuring out that something else is indeed possible. Taking Rodrik literally, it would mean also giving much more attention to what entrepreneurs are searching for and experimenting with in the background. It requires that we recognise that the current economy is creating what is viable under the current dynamic circumstances, and that only strategies that recognise where we are and what is certainly within reach from here is in fact viable. The challenge for developing economies is that what is possible is typically limited and further constrained by strong ideological bias as to what is possible or desirable. For instance, many South African business owners are trying to shift out of price sensitive markets competing on a basis of low cost skills. Entrepreneurs are moving into knowledge and capital intensive production, with more focus on service and integration. Government is searching for a way to employ people with low skills because its own social programmes and service delivery is not a viable fall back for people with insufficient skills.

The search is not about analysis
Complexity describes a situation where the patterns of what exactly is going on is unclear or shifting. We cannot entirely figure out what is leading to what and what is reinforcing what. Due to the dynamism, we cannot really understand the situation better through analysis. Another way of explaining this, is that a situation is complex when more than one competing hypothesis can with some probability explain what is going on. The only way to make sense of complexity is to try something, actually, try many things. And then see what seems to work better. It means that we start with what we have and who we know (and can trust), and then try a range of things with the simple purpose of seeing what is possible within the current constraints of the economic system. Steps must be taken to reduce risks (for instance by ensuring that the costs of failure are small, or that the experiments try different ways of solving the same problem), but then this whole approach in itself must be recognised to be politically risky.

This is where donors and development partners come in. By assisting developing countries to conduct low key experiments in order to create variety is essential, as development partners can reduce the political risks of their counterparts. This approach will furthermore require the abondenment of targets and indicators as an attempt to measure accountability and progress. A more subjective approach that sets indicators that monitors the overall health or dynamism is needed so that the experimentors can sense when they are indeed making progress. Thus the indicators does not measure success, nor input.

Perhaps then a skunkwork approach to a more complexity sensitive industrial policy approach is needed. Let the normal industrial policy targets and rigmarole be there. Politicions and bureacrats like this sense of certainty and purpose. But allow for some experimentation on the side under the heading “industrial policy research”. Allow this team to work with private sector partners to conduct small experiments to try new business models in an incremental way. For instance, do incubation to try new ways of mineral beneficiation, but without investing in large buildings or expensive equipment. Use what is existing as far as possible, even if it means having the manufacturing done on a contract basis elsewhere in order to test if local demand for the outputs exist.

The future aint what it seems

I have written many times before about my serendipitous journey into the topic of complexity. One of the important insights for me is that we cannot really predict much of the future under conditions of uncertainty. While there are many things for which we know what the consequences are, we have to acknowledge that there are many situations where we simply don’t know how things will turn out.

As I became more sensitive of the consequence of the insight about unpredictability I realized how much of my work hinged on assisting customers to somehow plot and engineer a specific future path. I moderate at least one strategy session for some or other developmentally minded organization every month, sometimes many times more. All these organizations want to set their portfolio of interventions into motion, and want to make sure their plans are foolproof and environment proof – meaning that failure can be avoided somehow.

Recently I started following Dave Snowden’s advice, assisting customers to have much deeper conversations about what is going on NOW, and what is possible NOW. We’ve been using the 3 Criteria for Quick Wins for a while (see note below), but now I emphasize living in the NOW. At first I felt a bit insecure to insist that we stop trying to focus on the ideal future, but now my confidence has grown. The amazing thing is that many of my customers are responding positively to this focus on what is possible now. Maybe it is more intuitive to work from the current. Maybe South Africa has become so complex that we can actually not afford to spend much time in the future.

I must add, we do still look at the future. I am not promoting a junkie style of optimizing the current without a view of the future. There are some things that we know about the future. For instance, if a University decides to increase investment in post graduate research, they know they will increase revenue, increase research outputs, without necessarily increasing fixed overheads. But we don’t set a high goal, set milestones and lunge into action. We start by saying “how does post graduate research work now?”. We explore the options, the possibilities and the obstacles. We also look at what we’ve tried in the past and whether the context has changed so that we can try a small experiment again. Then we develop a portfolio of small low risk interventions that can be executed simultaneously.

I have been following this approach for just a few months and I must admit that I am pleasantly surprised by the outcomes. Of course it felt weird in the start to leave customers with a portfolio of experiments instead of a clearly developed log-frame like project plan full of milestones, champions, indicators and deliverables. But I can see how my customers’ organizations have become a more healthy, balanced and perhaps even more naturally innovative.

The future ain’t what it seems because we have so many things we can do in the present. It takes real leadership to work with what we have and it takes real courage to break with the typical management-style of detailed project plans, log frames, project charts and the like.

 

Note about quick wins.

As Mesopartner, we define a quick win activity as one where:

1) The resources are within our control. This includes funding, but also key resources, key people and willing champions

2) The results are easy to communicate. Preferably the results are visual so that the benefits of change are disseminated easily to others.

3) We can take the first steps of implementation very soon, within days or weeks.

 

 

Industry development under conditions of complexity

Most economic development projects have a tendency to separate analysis from intervention or implementation. This follows on an engineering approach where you must first understand a problem or issue before you can design interventions which is then logically followed by implementation and later on evaluation. I will not now go off on why this logic is questionable as I have written about this before and we have dedicated the Systemic-Insight.com website to this topic.

But complexity thinking is challenging this norm of separating analysis and intervention.

Auwhere to gothors such as Snowden argues that under conditions of complexity, the best approach is to diagnose through intervention, which means that there is no real separation between diagnosis and intervention. Practically, you might have to spend some days and a little bit of effort to analyze who is interested in a particular issue so that you know where to start, but you have to recognize that even asking some simple questions is in itself already an intervention. Furthermore, the objective of working under conditions of complexity is to introduce more variety so that different approaches to overcoming constraints can be tried out simultaneously. This means that small portfolios of experiments must be developed and supported, trying many different ways to solve a problem. Many of these are guaranteed to fail, but new novelty will also arise. The health of a system depends on more options being proven viable. Strong alignment of interests, priorities and interventions are actually unhealthy for a system in the long run.

I’ve had this discussion many times with fellow practitioners in the last years and usually at some point somebody would say “but not everything is complex”. I agree. They would argue that there are definite casual relations between for instance education and economic development. Well, this may be true in some places. However, whenever a government (or a donor) decides that a particular sector or industry requires support it should assume that the issue is much more complex than it may appear, otherwise the industry actors and supporting organizations and demanding clients would have sorted things out by themselves.

The idea that diagnosis takes place during intervention has many detractors, despite the fact that many strong economic development organizations intuitively follows this process logic of working with diverse stakeholders in an ongoing process. Here is a short list of some of the detractors and their main reason for resisting such a process approach:

  • Large consulting firms: They would fight this approach as processes are much more difficult to quote and manage than a clearly defined project. Furthermore, this kind of approach depends on more expensive multidisciplinary experts that require a combination of technical, facilitation, change and business skills. The number of people that can support such a process are few and far in between.
  • The public sector: To overcome constraints created by complexity requires that dissent be nurtured and premature alignment be avoided. This is also risky for the public sector as things may not be so neat nor supportive of past policies and decisions. Furthermore, when more options are created it is not certain which firms will really take up the solutions – meaning that in a country like South Africa with strong benefit bias this is too risky, as preferred candidates might not be the beneficiaries of public support.
  • Donors and development organizations: Simple cause and effect interventions that depends on controlling certain inputs in order to benefit specific target groups still dominate the logic of donors. Therefore a process that is not specific, and that explores different alternatives may not be appealing to donors. Furthermore, donors are expected to be able to very precisely report not only in inputs, but also on impact. A process that has multiple shifting goal posts makes planning and resource management very difficult. However, many examples exist of donor supported projects that are very open to this approach, but this is mainly the prerogative of the programme managers deployed into the field – it is not systemic.
  • The private sector: Yes, even firms may resist an open ended and exploratory approach. One reason is that firms try to push the problems experienced in the private sector back onto the public sector (blame and responsibility shifting). An exploratory approach puts much more onus on the private sector to not only contribute, but to be open for alternatives and to then actively pursue opportunities that arise. Secondly, the incumbents in the private sector sometimes profits from a disorderly system. Many existing firms will resist newcomers trying different things and trying to create new markets, as this disrupts the way things are done at the moment. In a complexity sensitive approach we have to on purpose introduce novelty into the existing structures, and this means challenging some of the dominant views and agreements about what is going on, what must be done and why nothing has changed. This is very unsettling for the existing actors.
  • Top management in an organization: Management science in itself assumes many casual relations. For instance, strategy development typically starts with defining a vision and objectives, and then making sure that everyone is aligned and committed to these goals. As one of my favorite strategy David Maister argued  “strategy means saying no”. This means that resources are dedicated to a few specific areas in the belief that addressing these would have predictable and desirable effects.

Now I must state that in more ordered domains, where there is less complexity, many of the arguments outlined above are valid. In a small organization with limited resources priorities must be set. Governments cannot help everyone, so somehow a selection must be made. However, I believe that industry development is in many cases complex also because it is so hard to see how unpredictable effects will affect an industry.

I am grateful that I work with organizations that are willing to embark on industry development or institutional development processes that are more complexity sensitive. I believe that such an approach is particularly important for innovation systems promotion and for industrial policy. I am surprised at how many manufacturers and universities have agreed to embrace a more complexity sensitive approach to development, strategy formation and developing new services/products. All involved have been amazed at the early results this far, as these processes typically unleash a lot of energy and creativity by different stakeholders that in the past were more than willing to just observe from a distance what was going on.