Market systems are complex adaptive systems and market systems development is a complex task.

This abstract statement reflects the reality market systems practitioners encounter every day: market systems are dynamic with rich interactions between a large number of diverse actors. Changes in these systems are difficult to predict and development interventions often, if not always, lead to unintended consequences. 

Traditional development interventions don’t address everything
Yet a lot of the tools practitioners rely on are still deeply rooted in a mindset of predictability and control. Both the logframe and the often-used results chains, for example, are used to predict what a project will do and what will happen, step-by-step, as a consequence – they build a linear causal chain from input to impact. Linear tools to solve complex problems? I don’t believe so. Albert Einstein famously said something along the lines of: “We cannot solve our problems with the same type of thinking that created them.”

Logframes and results-chains, among many other tools, epitomise the current ‘type of thinking’ in development. The methods based in this linear, cause-and-effect paradigm have helped in many situations and improved millions of people’s lives around the planet. There remain, however, big challenges that these methods – and the thinking modes behind them – are not able to address. In some cases, the situations are made worse by the inappropriate way in which they are tackled. These challenges include the functioning of the markets and economies in many developing countries and countries in transition.

Effective intervention is seldom linear
I recently helped a programme in Myanmar that uses a market systems approach to develop a Theory of Systemic Change and intervention strategy. The project aims to improve the situation of small-holder rubber farmers in Mon State and adjacent areas of Myanmar. 

The exercise was an attempt to take into account the complexity of the rubber market. One of the important insights from thinking about complex adaptive systems we tried to apply in this project design is that systemic change does not happen in the form of a linear causal chain from one intervention to one systemic change. Rather, if we want to transform a market system, a number of interventions of the project, together with changes from other sources, will interact with each other and move the system along towards transformation in often unpredictable ways. 

Intervention effects are seldom linear. Some project interventions might be catalytic and lead to large-scale change. Some might not make any difference. But we cannot know that in advance. We further took into account the fact that complex systems contain different scales. To that we included interventions on:

  • the micro level, in which businesses interact
  • the meso level, which provides (or fails to provide) an enabling environment for businesses and markets
  • the macro level, which establishes the generic framework conditions
  • the meta level, which reflects social and cultural realities that influence the economic development trajectory

Doing Development Differently
But we are not the only ones who try to include complexity thinking in designing development programmes. In recent years, various actors in international development have recognised that a new way of doing development is needed, which led to movements like for example ‘Doing Development Differently’ to emerge.

Advocates for the new way of doing development promote:

  • adaptive programming instead of multi-year strategies
  • flexible planning and budgeting instead of rigid logframes and fixed budgets
  • a focus on feedback, adapting and learning rather than only accountability in monitoring change

Yet development actors are still far from effective in applying complexity thinking in strategy development, operational programming and, indeed, day-to-day work. Practical experience remains limited. Besides the general lack of opportunities to build personal and organisational capacity in harnessing the power of complexity thinking, the organisational structures in both public and private development organisations often hinders the introduction of the new type of thinking.

A new training course to change systems
At Mesopartner, we have been learning about and applying complexity thinking in economic development for over a decade. Together with Tony Quinlan from Narrate, a seasoned complexity expert and practitioner, we have now put together a new training course specifically for development practitioners that aims to change systems – such as market systems. The course aims to introduce this new kind of thinking that we believe will help development practitioners become more effective in achieving systemic change.

When we started thinking about the course we knew that we did not want to develop a conventional training event. During such events, trainers usually download a lot of theories, concepts, framework, tools and case studies onto participants. They then leave them alone to try to make sense of it all -  how it relates to their own work, and how they can apply this new knowledge.

So, what we have come up with is a three-month programme. It combines inputs with experiential parts during which the participants will be able to apply the new ideas to concrete, real-world problems taken from their own contexts.

We are very excited about this structure as we believe it will allow participants to effectively combine conceptual/theoretical inputs with experiential learning on real-world issues. The training is aimed to be an expedition and exploration into complexity that allows for the unexpected to emerge. It will be adaptive enough to accommodate for course corrections en route.

We hope that during the three months spent together, the group of participants will grow into a peer-support network that will continue to support each other after the training concludes. While we will provide the initial platform to do that, this network will essentially have to be self-organised by the participants – self-organisation obviously being a core-concept in complexity!

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