Category: Process and Change Facilitation

Identifying firms to work with to induce upgrading of industries

This is a revised edition of a blog post I wrote back in 2011.

When working on the improvement of innovation systems in developing countries, we have to work with firms. These firms have several roles, and there are three units of analysis:

  1. The firm is an important unit of analysis of innovative practices (product, process, business model).
  2. The firm is also a unit of analysis in terms of cooperation and collaboration, thus its ability to cooperate with rivals is an important consideration when we design interventions.
  3. Working with the right firms also provides an important source of technology and knowledge spillovers. This is where the challenge comes in for development practitioners.

Generally, firms that are able to lead the way, or could be good role models, are difficult to involve in development programmes for a variety of reasons. I won’t discuss that right now. What is important to remember is that most firms not only absorb or use technology and knowledge, they are also the main sources of knowledge and technology. This is both from a supply perspective (equipment suppliers, technical or specialist sources of knowledge, etc.) and from a demand perspective (demanding customers, sophisticated demand). Whether firms are aware of their role as disseminators of knowledge of technology is another story!

I will rather focus on how to identify the firms that we can work with to improve innovation and competence in all three units of analysis discussed above. Remember, our objective is to find ways to improve the dynamic in innovation systems that will result in the modernisation and technological upgrading of industries and regions.

More than 25 years ago Bo Carlsson and Gunnar Eliasson described a concept called “economic competence”. At the time they defined economic competence as “the ability to identify, expand and exploit business opportunities” (Carlsson and Eliasson, 1991). This is a useful definition as we have to remember that we cannot innovate on behalf of a broader industry. Somehow we must work with those firms that are able to innovate, imitate, adapt and integrate new knowledge and ideas.

According to Carlsson and Eliasson, economic or business competence has four main components:

  1. Selective (strategic) capability: the ability to make innovative choices of markets, products, technologies and overall organisational structure; to engage in entrepreneurial activity; and especially to select key personnel and acquire key resources, including new competence. This aspect has been amply illustrated in recent years as many companies have struggled to define their corporate identities and strategies as distinct from their competitive strategies in each individual business unit (Porter, 1991).
  2. Organisational (integrative, coordinating) capability: the ability to organise the business units in such a way that there is greater value in the corporate entity as a whole than in the sum of the individual parts.
  3. Technical (functional) ability: this relates to the various functions within the firm, such as production, marketing, engineering, research and development, as well as product-specific capabilities. These are the areas of activity in which firms can compare themselves to their peers or leading competitors.
  4. Learning ability, or the shaping of a corporate culture which encourages continual change in response to changes in the environment.

Economic competence must be present in sufficient quantity and quality on the part of all relevant economic agents, users as well as suppliers, government agents, etc. in order for the technological system to function well. This is both true at a local or regional level, our a national or sectoral level.

If the buyers are not competent to demand or use new technology – or alternatively, if the suppliers are not able or willing to supply it – even a major technical breakthrough has no practical value or may even have negative value if competitors are quicker to take advantage of it.

I think that this business approach of choosing the entrepreneurs that we work with is very relevant to finding the people who can absorb new ideas and make them work in a developing country context. I would also go so far as to state that I do not believe that it is feasible to select “change agents” according to social criteria such as gender, age, etc. – but that we recognise that change within economic systems happens because of the economic competencies of the people who are recognised in the system (regardless of their demographic data). The reality is that you cannot be competent on behalf of other people!

I challenge you to review the firms that you are working with to see if they are economically competent!

Sources:

Carlsson, B. and Eliasson, G. (1991). The nature and importance of economic competence. Working Paper No. 294, The Industrial Institute for Economic and Social Research (IUI).

Porter, M.E. (1991). “Towards a dynamic theory of strategy“, Strategic Management Journal, 12 (Winter Special Issue), pp. 95-117.

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.

Instigating Innovation: Accelerating Experimentation in industry

Originally published Feb 2016, revised March 2018

When innovation centres, technology transfer centres, applied research platforms and other similar organisations wish to help industry with innovation, one way could be to assist companies to experiment with new ideas. I will simply refer to these centres from now on as innovation and technology support centres. In most of the places where I work these centres are often hosted by or associated with universities, applied research organisations or technology transfer organisations.

One way to support industry to experiment is through various technology demonstration-like activities, allowing enterprises access to scarce and sophisticated equipment where they can try out new ideas. In its simplest form, a facility allows a company to order samples to a certain specification so that the company can see whether a particular process will be able to meet a particular specification or performance criterion. A slightly more intensive form of technology demonstration allows visitors in and a technology and its application is demonstrated (eyes only, no touching!). Very often equipment suppliers play this role, but in many developing countries equipment suppliers act more as agents and cannot really demonstrate equipment.

In Germany I saw demonstration facilities where the pro’s showed the enterprises how things work, and then they stood back to allow teams from companies to try things out themselves.

A critical role of innovation support centres is to provide industry with comparative studies of different process equipment. For instance, an innovation centre supporting metal-based manufacturers, providing the industry with a comparison of the costs and uses of different kinds of CAD systems could be extremely valuable to the industry.

Maker labs, Fablabs and similar centres all make it easier for teams that want to create or tinker with an idea to have access to diverse technologies, reducing the costs of experimenting. However, the equipment in these labs is often not so advanced, but it can often be very diversified. In my experience these centres are very helpful when it comes to refining early idea formation and prototyping. However, helping manufacturers to experiment with different process technologies, different kinds of materials, substitute technologies, etc. is a binding constraint in many developing countries. The costs of gaining new knowledge is high, and the high costs of failure make companies wary of experimenting.

Innovation support centres must be very intentional about reducing the costs of various kinds of experiment if they want manufacturers, emerging enterprises and inventors to try new ideas. These innovation centres can play a role by:

a) assisting companies to organize themselves better for experimentation internally

b) assisting many companies to organize themselves better for experimentation collaboratively

c) conducting transparent experiments on behalf of industry collectives.

In my experience, graduates from science disciplines often understand how to conduct experiments because their course work often involves time in a lab. They know basics such as isolating variables, managing samples, measuring results, etc. However, engineering graduates often do not have this experience (at least in the countries where I have mostly been working). The closest many engineering graduates will ever get to an experiment is a CAD design or perhaps a 3D printed prototype.

Therefore it is necessary for a range of these innovation and technology support centres to assist companies at various hierarchical levels to experiment.

At the functional or operational level, organising for experimentation involves:

  • creating teams from different operational backgrounds
  • creating multiple teams working on the same problem
  • getting different teams to pursue different approaches
  • failing in parallel and then regularly comparing results
  • failing faster by using iterations, physical prototypes and mock-ups.

According to Thomke, results should be anticipated and exploited – even before the results are confirmed.

At a higher management level, organising for experimentation involves:

  • Changing measurement systems not only to reward success, but to encourage the trying of new things (thus encouraging learning and not discouraging failure).
  • Moving from expert opinion to allow naivety and creativity.
  • Preparing for ideas and results that may point to management failures or inefficiencies elsewhere in the firm (e.g. improving a process may be hampered by a company policy from the finance department).

Getting multiple companies and supporting organisations to experiment together is of course a little more difficult. Management of different organisations have many reasons to conceal failures, thus undermining collective learning. One way around this could be to use a panel or collective of companies to identify a range of experiments, and then to have these experiments conducted at the supporting institution in a transparent way. All the results (successes, failures and variable results) are carefully documented and shared with the companies. However, to get the manufacturers to use these new ideas may require some incentives. In my experience, this works much better in a competitive environment, where companies are under pressure to use new ideas to gain an advantage. In industries with poor dynamism and low competition, new ideas are often not leveraged because it simply takes too much effort to be different.

Promising ideas from experiments can be combined and integrated after several iterations to create working prototypes. Here the challenge is to help industries to think small. First get the prototype process to work on a small scale and at lower cost before going to large scale of testing several variables simultaneously. An important heuristic is to prototype on as small a scale as possible while keeping the key mechanical or scientific properties consistent. More about this in a later post. (Or perhaps some of the people I have helped recently would not mind sharing their experience in the comments section?)

I know that this is already a long post, but I should like to add that Dave Snowden promotes Safe2fail probes, where teams are forced to design a range of experiments going in a variety of directions even if failure is certain in some instances. In my experience this really works well. It breaks the linear thinking that often dominates the technical and manufacturing industries by acknowledging that, while there may be preferred solutions, alternatives and especially naive experiments should be included in the overall portfolio. To make this work it is really important that the teams report back regularly on their learning and results, and that all the teams together decide which solutions worked best within the context.

 

Source:

THOMKE, S.H. 2003.  Experimentation matters: Unlocking the potential of new technologies for innovation. Harvard Business Press.

 

 

Instigating innovation in traditional industries

Originally published in January 2016, revised in March 2018

The average manufacturer in a developing country often grapples with the notion of innovation. That is why such industries are often called “traditional“, although almost all industries will have one or two outliers. While governments, such as the South African government, offer incentives to stimulate innovation, most manufacturers do not identify with the term “innovation” the way governments use it. For instance, when governments use the word “innovation” they often mean “invention“, in other words something that can be protected, copyrighted and owned (see more about the differences between innovation and invention here). While I understand the argument for patenting and protection, I think this narrow definition of innovation is inhibiting many industries from increasing their productivity and competitiveness by copying what works elsewhere (this is just a process of catching up). It also fails to recognize that in many value chains the manufacturers themselves make components or sub-systems that go into overarching architectures (defined by standards, compliance, specifications), so their design authority is limited in scope.

Innovation_invention

Here is a list of synonyms from thesaurus.com for innovation that I have assessed to see how enterprises might understand or react to these words:

  • Modernization – many enterprises dream about this but often do not have the financial means nor the organizational capability to pull it off (one day, some other time)
  • Contraption – many innovations and most inventions result in one of these. You can see them standing in  corners in most factories
  • Mutation, addition, alteration, modification – this is what most innovations in traditional industry would look like. They are doing this all the time as their machines get older, but this behaviour is mostly not recognized nor speeded up.
  • Newness, departure, deviation – the bolder enterprises with more financial and organizational capability might try these, but it takes capital to maintain.

Most people understand innovation as an outcome, but the word is a noun that implies change and novelty. It is about a shift, even if it is often incremental. The reason why so many of our enterprises in South Africa are not regarded as innovative is because they struggle (or perhaps do not have the organizational capability) to manage several simultaneous change processes. As Tim Kastelle posted some years ago, change is simple but not easy. Although this is often described as a technology problem it is really a management problem (see some older posts here). I would go even further and state that in many industries the margins are so narrow that even those enterprises that have a reasonable management structure would struggle to finance many innovations at the same time.

However, in my experience of having visited more than 50 manufacturers every year since 2009, I am always stunned and awed by how ingenious these companies can be. They keep old machines running, often modifying them on the fly. They operate with a fluctuating and unreliable electricity supply, inconsistent water pressure and often hardly any technical support. What policy makers often do not realize is that in developing countries it takes a lot of management time and capacity just to keep the throughput going. The time and effort to go and explore “change” beyond what is necessary in the short to medium term is very costly. The costs of evaluating new ideas, new technologies, new markets and better suppliers are all far greater in developing countries than in developed countries. Yet at the heart of innovation is the ability to combine different inputs, different knowledge pools, and different supporting capabilities with different market possibilities.

There are two implications for innovation promotion practitioners.

  1. The process of instigating innovation must start with recognizing how companies are innovating NOW. How are they modifying their processes (and products), and how much does it cost? What are the risks that are keeping them from introducing more novelty? Perhaps they could use the Horizons of Innovation to create a portfolio of innovation (change) activities that can be identified at the enterprise or industry levels.
  2. It is hard if not impossible for different manufacturers in most countries to figure out what others are struggling to change at a technological level. Use your ability to move between enterprises to identify opportunities to turn individual company costs into public costs (this is often cheaper). Do not take the innovation away from enterprises, but use your meso level technology institutions to try and accelerate the learning or to reduce the costs of trying various alternatives. Be very open with the results to enable learning and dissemination of ideas.

The process of instigating innovation must start with recognizing where manufacturers are naturally trying to change, just as a change process in an organization must start with understanding current behaviour, culture and context. Somehow innovation has become so associated with contraptions and narrow views of technology that the body of knowledge of organizational development and management of change have been left behind.

Innovation systems in Metropolitan Regions of developing countries

During 2015 Frank Waeltring and I were commissioned by the GIZ Sector Project “Sustainable Development of Metropolitan Regions” (on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), Division 312 – Water, Urban Development, Transport) to write a discussion paper about a hands-on approach to innovation systems promotion in metropolitan regions in developing countries. The discussion paper can be found here.

Frank (left) and Shawn (right) in front of the Berlin Wall Memorial

This assignment was a great opportunity for us to reflect on Frank’s experience on structural change in territorial economic development and my experience on industrialization and innovation systems in developing countries. We also had to think hard about some of the challenges of using a bottom up innovation systems logic in developing countries, as such an approach would rely heavily on the ability of local public management to coordinate strategic activities aimed to improve the dynamics between various public and private stakeholders. It was great to reflect on our past Local Economic Development experience and our more recent work on innovation systems, industrial upgrading and complexity thinking.

A key aspect of this discussion document was to think long and hard about where to start. We know many economic development practitioners in cities are often overrun by demands from both politicians and industries for support. We also know that by selecting promising sectors based on past data and assumptions about job and wealth creation often end in little impact and much frustration. We agreed that an innovation systems approach must be aimed at stimulating the innovative use of knowledge, so we decided to not start with a demand focus (assuming the officials are already responding to some of the demand) or with statistics but a knowledge application focus. The use, generation and recombination of knowledge is central to the technological upgrading of regions, industries, institutions and societies. From our experience in promoting innovation systems and our recent research into non-consensus based decision making (this is where you do not select target sectors based on consensus or assumptions about growth potential, but you look at emergent properties in the system) we decided to start with three questions to understand the dynamics of knowledge flows in the region:

  1. Which enterprises, organisations and even individuals are using knowledge in an innovative way? Obviously this question is not simple and can only be answered by reaching out in the local economy to institutions, firms and individuals.
  2. Which stakeholders are actively accumulating knowledge from local or external sources? Again, this is an exploration.
  3. Who are individuals or organisations that know something about unique problems (challenges, demands, constraints) in the region? These could be buyers, supply chain development officials, public officials, engineers or even politicians that are willing to articulate unique demands on the regional economy that might not have been responded on by local (or external) enterprises.

These three questions are treated as an exploration that will most likely be most intensive at the start. In our experience economic development practitioners should constantly be asking themselves these questions when working on any form of private sector upgrading.

A second dimension is about assessing the interplay between institutions and industries and its effect on innovative behavior within regions. Who is working with whom on what? Why? What are the characteristics of the life cycles or maturity of various kinds of stakeholders in the region? Thus we are trying to understand how knowledge “flows” or is disseminated in the region. While some knowledge flows are obvious, perhaps even formal, some knowledge flows could be more tacit and informal. For instance, while knowledge flows from education is quite formal, the informal knowledge exchange that takes place at social events is much more informal, yet very important.

Apart from the identification of the dynamics and interrelations between the industries and the different locations, one other key factor is to identify the drivers of change who want to develop the competitive advantages of the region.

We also present our technological capability upgrading approach as six lines of inquiry, some of which have been covered in earlier posts on this weblog:

  1. The company-level innovation capability and the incentives of firms to innovate, compete, collaborate and improve, in other words the firm-level factors affecting the performance of firms and their net-works of customers and suppliers. These include attempts within firms to become more competitive and also attempts between firms to cooperate on issues such as skills development, R&D, etc.
  2. The macroeconomic, regulatory, political and other framework conditions that shape the incentives of enterprises and institutions to develop technological capability and to be innovative.
  3. Investigation of the technological institutions that disseminate knowledge.
  4. The responsiveness and contribution of training and education organisations in building the capacity of industry, employees and society at large.
  5. Investigation not only of the interaction and dynamics between individual elements in the system, but of the whole system.
  6. Exploring poorly articulated needs or unmet demands that are not visibly pursued by the innovation system.

We, and of course our GIZ colleagues of the Sector Project Sustainable Development of Metropolitan Regions, are very keen to engage with the readers on these ideas? Please post your comments, questions to this weblog so that we can have a discussion.

Best wishes, Shawn and Frank (Mesopartner)

 

 

New series: Instigating Innovation

I have been developing a new capacity building method and training approach that brings together my work in innovation systems promotion  and my work on improving technology and innovation management. I call it “Instigating Innovation”.

I chose “instigating” because it has a more positive ring to it than provocation or incitement. While it is a noun with mainly a positive tone, it is a bit more aggressive than support, enable or encourage or even stimulating. I have been referred to in my past as an instigator of change so I thought this was a good idea.

Why was this effort firstly necessary and secondary so rewarding?

My work on innovation systems is mainly aimed at assisting meso-organizations such as technology transfer centres, research centres and universities to be more responsive to the needs of the private sector. While it only takes a few interviews by a senior decision maker from one of these institutions to a few leading enterprises to get the organization to improve its offering to the private sector, it does not solve the problem that these institutions often needs a continuous process of innovation itself. So while they can respond to the needs of the enterprises (for instance by launching a new service, or making a key technology available, etc), they often are not able to innovate constantly in order to anticipate what they private sector might need in the future.

With my other hat on, working in the private sector to improve the management of technology and innovation is focused on helping individual and on rare occasions, groups or networks of enterprises to formalize or improve their management of innovation. Here my challenge is that most enterprises innovate by accident, or have elements of an innovation management approach in place without knowing it. But it is not systematic nor is it consistent.

So both supporting institutions and enterprises lack some very basic frameworks to focus their existing development and learning processes to ensure not only short term results (new products & services, process improvements, cost reduction, etc) but to also ensure longer term success (playing in the right markets, selecting the right technologies, investing in the right kind of knowledge, partnering with the right people, etc). Furthermore, most enterprises and supporting institutions have something else in common: they often face resource constraints with the most versatile of their staff being involved in problem solving and not thinking about the future and what may be possible sometime down the line.

I set aside most of March and had great fun reading through my collection of articles, books, reports of past missions, and speaking to entrepreneurs and development practitioners I trust. Based on this investigation I decided on the following criteria for instruments to include in the Instigating Innovation module:

  1. Each instrument or concept must be relevant to both enterprises and meso-level organizations05 building innovative capacity small
  2. Each instrument must provide a very simple framework that can be illustrated on a flipchart
  3. The simple framework must be usable as a workshop format that allows people to reorganize or explore their current and future practices
  4. The frameworks must be scalable, both in depth (allowing pointers for a deep dive into an issue) and in width (useable for a product, issue, portfolio or the strategy of the organization as a whole).
  5. Lastly, I did not want to be the consultant with a project, I want to be the facilitator that enables change and that builds long term sustainability into the organizations that I work with.

This was a very rewarding exercise. Not only do I love reading about innovation, change and technology, I love finding better ways to explain these concepts. It was also great to find a way to connect my work on innovation systems, which often seems abstract, with the tough decisions that the enterprises that I work with must confront and address. I tend to work in the more technical domains dominated by academics, engineers, scientists and manufacturers, so finding a simple yet convincing way to add value to what these clever people do was important.

I will in the next few posts reveal a little bit more of the tools I selected and how it can be used.

Thank you for the EDA team in Bosnia and Herzegovina who motivated me to turn this idea into a capacity building format and who agreed that I try “Instigating Innovation” on their team during my visit to Banja Luka in May 2015!

Instigating Innovation in Banja Luka with the team from EDA
Instigating Innovation in Banja Luka with the team from EDA

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.

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.

Recognizing competing hypothesis as complex

In order to improve the economic performance of an industry or a territory, it is important to recognize the current Status Quo of the economy. This is basically to understand “what is?”, but to also understand “what is possible next?”. You may think that local stakeholders, firms and public officials will know the answer to “what is going on now?”, but every time I have done such an assessment I have discovered new suppliers, new innovations, new demands and many new connections between different actors.

The benefit of being a facilitator, process consultant or development expert, is that we can move between different actors, observe certain trends, recognize gaps and form an overall picture of what we think is going on. It is very difficult for enterprises to form such a picture as they can only observe other firms from a distance.

The main challenge is about figuring out what can be done to improve certain gaps or to change the patterns that we observe. These are answers to “What is possible next?” questions . As Mesopartner, we always insist that any process to diagnose an industry or a region starts with the formulation of various hypothesis. This hypothesis formulation before we commence is not only about revealing our bias, nor only about figuring out what exactly we want to find out. It also helps us to figure out what kind of process is needed, the scope of the analysis and what different actors expect from the process.

Unlike in academic or scientific research, hypothesis formulation does not only happen in the early stages of a diagnostic or improvement process, it should be constantly reflected upon and expanded as we go on during the process of meeting stakeholders and analyzing data. This is where the importance of recognizing competing hypothesis within our team and between different stakeholders are important.This process is not about convergence, but about revealing what different actors and the investigator believes is going on.

Economic development practice is full of competing hypothesis that all seem to be very plausible. In a recent training event with Dave Snowden the consequences of not recognizing or revealing these competing hypothesis struck me. According to Dave, competing hypothesis that plausibly explains the same phenomena indicates that we are most likely dealing with a complex issue. For instance, in South Africa we have competing hypothesis about the role of small firms in the economy. One hypothesis is that small firms are engines of growth and innovation, therefore they deserve support. A competing hypothesis is that large firms invest more in innovation and growth, and that they are better drivers of economic growth. Both hypotheses are plausible – the issue is complex. Recognizing this complexity is very important, as the cause and effect relations are not easy to identify and they might even be changing – the situation is non-linear. (Marcus Jenal and I wrote a working paper on complexity in development). This simply means that to get a specific outcome, the path will most likely be indirect or oblique – cause and effect is not linear.

Why is it important to recognize competing hypothesis, or to know when some patterns in the economy or complex? The answer is that it is almost impossible to analyze a complex issue with normal diagnostic instruments. Complex patterns can only be understood by engagement, that is, through experimentation. Again, according to Dave Snowden, you have to probe a complex issue by trying several different possible fixes simultaneously, then observe (sense) what seems to work best under the current circumstances. The bottom line is that you analyze a complex issue by experimenting with it, not by observing or analyzing it.

The implication of this insight in my own work has been huge. By recognizing that many issues that I am dealing with are complex (due to competing hypothesis that are very plausible) and can only be addressed through direct engagement has saved me and my customers a lot of resources that was previously spent on seemingly circular analysis. I now use the hypothesis formation with my clients to try and see if we have competing hypothesis of “what is” and “what must be done”. Where the hypothesis seems to be straight forward, we can define a research process to reveal what is going on and what can be done to improve the situation. But when we have different competing hypothesis of what is going on, we have to immediately devise several simultaneous experiments to try and find an upgrading path. I thought my customers would not like the idea of experiments, but I was wrong.

The conditions are that you must take steps to ensure that there are many different experiments that are all very small, and that by design take different approaches to try and solve the same problem. This takes learning by doing to a new level – because now failure is as important as success as it helps us to find the paths to better performance by reducing alternatives and finding the factors in the context that makes progress possible. The biggest surprise for me is that this process of purposeful small experiments to see what is possible under current conditions (context) has unlocked my own and my customers creativity.

Perhaps a topic for a separate blog is that to really uncover these competing hypothesis we have to make sure that we do not converge too soon about what we think is going on. Maintaining divergence and variety is key – this is another challenge for me as a facilitator that is used to helping minds meet!