Complexity and Evolutionary Thinking Links

Linking: Gregory Mankiw article “when the scientist is also a philosopher”

In the last two years we (Mesopartner) have been exploring how complexity science affects development practice. Well, we were quite shocked to realize how much of development is based on preference and bias, and how little is actually based on proper scientific research. Frequently practitioners takes little bits and pieces of different theoretical bases to create a construct of an approach that is suitable to them because it meets their own hypotheses of how the world works. It is important also to not confuse evidence based monitoring and evaluation with scientific evidence.

The famous economic thinker, Gregory Mankiw, has published an article in the New York Times where he goes into this topic with his usual easy to understand arguments. The title of his article is “when the scientist is also a philosopher”. He argues that a danger of economics (I would argue of all economic development) is that we are not aware of our bias, and we do not depend on proper scientific methods. He recommends that we offer our advice with a healthy dose of humility, as we are often not aware of how complex the economy is and how our advice will affect other systems, or whether our advice will work at all.

Gregory Mankiw was a great inspiration for me during my PhD research and I am grateful to have stumbled across this article. He is currently an economics professor at Harvard.

Complexity and Evolutionary Thinking

Recent Mesopartner Working paper on complexity theory and development

This article was originally posted by Marcus Jenal on the website in December 2013. I co-authored this paper with Marcus. It is an output of the theme of applying complexity theories to economic development.

For the last 3 years we at Mesopartner have been purposefully experimenting with complexity and systems theories in our practice. Not only did we change our company logo and strapline based on our new learning, we started to dismantle and question almost every aspect of our instruments, tools and theories.

This was a steep learning curve for us and for our key customers who agreed that we could embark on these serendipitous journeys together. While we still believe in bottom up development, we are wondering about how to achieve developmental change within the typical timelines and resource constraints that development projects often face.

One of the results of this process is this website (, where we want to share our thoughts and invite our followers to contribute to the discussions we have.

A new Mesopartner working paper now provides a theoretical grounding for the work we have done in the last three years and will continue to do. We consider some definitions, ponder the implications and try to formulate some responses to some of the key challenges that systems and complexity theories confront us with in our field of bottom up economic development.

We see this paper as an input into a broader discussion with our close collaborators, our close clients, and the broader network that we form part of. We ask  you to send us your thoughts and add your comments to this and future posts.

We thank the colleagues that have already commented on the paper. Many of the suggestions are already incorporated into this version. Your contributions are greatly appreciated. Shawn and Marcus

Complexity and Evolutionary Thinking Promoting Innovation Systems Thinking out loud

Thinking out loud: Is aid systematically unsystemic?

Originally published on 26 August 2013, edited and republished on 23 July 2019

I am taking a risk with this post, but I am sure my regular readers will bear with me as I think out loud. I have been fortunate in the past few months to have been able to focus my praxis almost completely on the topic of complexity and systems thinking in development, with a particular emphasis on innovation systems and the technological evolution of industries and regions. Shifting from advocating for a different approach to actually assisting with the shift has been a really exciting venture.

Disclaimer: These are my own opinions and do not reflect Mesopartner’s views. 

Systems and complexity thinking is now central to Mesopartner’s,  work (see our Systemic-Insight theme page). Not surprisingly, my main customers for working on systems and complexity are not those involved with development programmes per se, but meso level institutions tasked with supporting industries and sub-sectors to innovate, grow, compete and increase employment. It is no secret to most of you that I am very disillusioned with aid and development cooperation at the moment.

When you dive into the literature on complex adaptive systems and how they tend to function naturally, you cannot help but wonder whether aid and development cooperation is in a very systematic way trying to fight the very things that make economic systems so amazing. There are several universal phenomena about complex systems that seem to be ignored (I will highlight just a few that I found personally the most challenging to deal with in my work):

  • In complex systems, resources are allocated (or taken up) by those best able to make sense of the situation, using a combination of knowledge, resources and past experience. Marcus Jenal reminded me that people also exercise power and use their influence to take up these resources. It is a reinforcing loop referred to by systems thinkers such as Donnella Meadows as “strength to the strong”. It is even mentioned in the Bible and in other spiritual and philosophical texts. This presents us with the first dilemma as we can often sense that the way resources are distributed is not fair or just, and that many agents in the system will resist any attempt at redistribution.
  • Even when systems become unstable, they do tend to find a kind of equilibrium range. This means that systems will by their very nature resist our interventions as they strive towards some natural range.
  • When a system remains in a suboptimal state (in our judgement it is not delivering what we think it should deliver), we can almost be certain that somebody somewhere is using their power or influence to keep the system in a suboptimal state to extract rents from the situation. It is unnatural for systems to remain “broken” over an extended period without someone influential in the system benefitting from it.
  • Related to the previous point, the ability of an external agent to assess whether a system is broken is debatable and not questioned often enough. Even if the actors in the system believe it is broken, the system might just be behaving in a very natural way. Examples can be found in finance (who wants to lend money to potential losers when they can guarantee returns rather by lending to potential winners) or in agriculture (brokers overcome scale and uncertainty by aggregating volumes, and in return for their risk they earn good profits). There is a second dimension to this: if we ask the actors in the system what is bothering them, they will in most cases shift the blame for their decision or indecision somewhere else.
  • What is good for the system is not always good for the agents in the system and the other way around. An example is that strategies to promote exports or employment growth might actually have a negative effect on many small enterprises while having a positive effect on medium and large-sized enterprises. Or strengthening smaller enterprises might have a negative effect on the current account (through increased imports) while at the same increasing jobs in the service sector.
  • One of the weakest points of influence in a system is the actor, while one of the strongest leverage points is the purpose (often not articulated formally) and the rules (social institutions) of the system. Although it is much harder to change, the purpose of the system is the most important leverage point, followed by rules and the nature and frequency of interrelations. Yet most development programmes target particular actors, ignoring the implicit or unexpressed meta-purpose of the system. Furthermore, most measurement systems measure outputs at the level of the actor, instead of monitoring behaviour in the system. Behaviour (informed by social rules) is a better (yet harder to quantify) measure as it tells us something about the purpose, the meta culture and actors’ attitude towards his or her own health and the health of the systems. This is also a characteristic that I find personally challenging, as it takes time to change the purpose and the rules of the system. In many cases, people simply cannot even explain the purpose of their systems or the rules they follow, which are instinctively based on their values. Changing the purpose of a system requires people to change their priorities, their values, the way to judge success (or failure) and the way they perceive their role in a system or society.
  • There is a relationship between the actors and their artifacts (equipment, assets, machines, tools, etc,). Old, broken or outdated equipment is a symptom of old, broken and outdated business models implemented or executed by the actors. Somehow this is made possible by both the social context and the social as well as the economic technologies. Giving an actor a new artifact (equipment) does not necessarily change the system in the long term, as the actor is still the same. I have often witnessed how an old factory with outdated equipment but that is managed properly can outperform a modern factory run by incompetent management (management itself is an economic and social technology). Providing incentives for an existing business to buy new equipment is to address a symptom and not a cause of sustained underperformance. But an existing actor with a new attitude, better information or different behaviour is able to use existing artifacts more effectively. In the real world, this means that upgrading the equipment in a business is the wrong place to start. Rather promote new entrepreneurs or people who can better use the existing equipment. Physical technologies co-evolve with economic and social technologies; we are not dealing with an equipment problem only.

How do we get development programmes to embrace some of the strengths of complex systems? For example:

  • In complex systems, agents make decisions in a decentralised way. They make these decisions based on their perceptions of their environment and their perceptions of alternative futures, based on the information at their disposal. Thus flooding the system with valid information and promoting the view of how new knowledge or technologies can increase returns is much more valuable than physically trying to fix the actor. Education, technology demonstration and supporting experimentation are ways to provide entrepreneurs with better information to support decision making. It is often very difficult in developing countries to find this type of information which is needed for decision making support by entrepreneurs or firms.
  • A complex system exists of agents(or actors)and their artifacts, the interrelations between the agents and their common (system) purpose. Often in development, we describe only the actors, while ignoring the fact that a system has other elements that are important to include in our description. Already describing a target system as “small farmers using outdated equipment advocating for state protection” is already a much better description of a typical system, as opposed to “poor small farmers who are suffering”. We can also not just focus on “technology” without considering social and economic technologies.
  • In complex systems, the behaviour of the system emerges from the behaviour of all the elements in the systemThis emerging behaviour, in turn, has an effect on all the elements in the system, which gives rise to complexity. In complex systems there are strong feedback loops between the elements in the system and the overall observed behaviour or purpose of the system. As economies become more complex, and as inter-dependencies between different systems increase, so too it becomes more difficult to predict or anticipate how a system will change, adapt or respond to a change. This means that we have to be more sensitive to the feedback loops. Our greatest weakness is that we are outside the system, but this can also be turned into a strength if we use our distance to provide a neutral perspective on how the system seems to be behaving.
  • Even if we acknowledge that complex systems also frequently resist change, it is necessary to acknowledge that complex systems are very sensitive to small changes. Can we identify the areas where the system is least resistant to change? Can we support small safe-to-fail experiments in the areas where the risks seem high? Can we help the system to develop alternative paths that the actors can try out? Let us make sure that we increase the options available to the stakeholders and NOT fall in the trap of pushing stakeholders to adopt a “silver bullet” approach.
  • In complex systems, proximity (closeness) and connectivity (social networks) really matter. Every agent is connected to other agents and to the greater system in many different ways, and each agent typically affects every other agent through their effect on the system and their close neighbours in the system. The behaviour of any given actor affects the perspective and behaviour of other actors who are close to them. This means that we should also work with the existing structures and not create new artificial networks. If your first instinct is that the stakeholders are poorly coordinated and therefore that more coordination is needed, then you are pushing the system in the wrong direction.
  • The starting state really matters. And so does the development or evolutionary past of the system. The history of the system is still very evident in the system, and it affects how the system responds to choices, opportunities, failures and challenges. Thus the future of the system is affected by its past in unpredictable ways. This is why a solution that works in one place will almost certainly not work in another.
  • In complex systems, correlations may be strong, but causation is weak or hard to identify with certainty. In fact, what caused a particular response in the past might have no effect in the future, so perhaps trying to understand causation is in itself a future exercise. It is often impossible to figure out cause and effect and its direction in a complex system. We should not propose interventions with “guaranteed” linear outcomes. We should rather use our resources to assist developing countries to try different ideas by assisting in the creation of multiple viable paths. This is a task with very uncertain outcomes, which is exactly why our counterparts don’t pursue these risky options.

For me, development cooperation and aid need to embrace the principles of complex systems. Dave Snowden, in a Cynefin training arranged by Mesopartner in 2013, commented: “you absorb complexity, you don’t delude yourself into thinking you can eliminate it”. What I am really surprised at is how my clients in the public sector meso institutions and in the private sector find it easy to embrace the principles of complexity, while development programmes resist these same ideas. For so many of the private sector people with whom I am now working, these principles are useful as they help to explain why certain well-intentioned interventions did not yield the expected results.

My frustration is that when we discuss these same principles with aid partners or development cooperation programmes which support the very same institutions with which I am working, they find many excuses for not embracing these principles. For instance, last week I was told that “we need a clear project plan (a.k.a. an impact chain), based on a detailed assessment so that we can precisely measure our impact. We need to clearly state and then work towards our indicators so that we have evidence that we have achieved change”. Read that sentence again and count the number of times “we” and “our” are used. It seems to me that development is about delivery or applying resources and not about supporting the evolution and expansion of complex economic systems in developing countries. Never mind how sceptical development organisations are about the insights of local stakeholders as to what is really going on in the system, and how confident they are that they know exactly what the problem and the solution are.

I cannot help but wonder whether aid and development cooperation is systemically unsystemic.

23-07-2019 comment by Shawn. I decided to re-publish this post as I still find the same patterns in development. As a team, Mesopartner has moved deep into complexity thinking and have made profound changes to our consulting practice, research themes and capacity building events. Yet, much remains to be done. We are constantly also challenged by our clients in development who have to meet their funder’s requirements for predictable and quantifiable results, despite the people in these development organisations knowing that their interventions might not be addressing the real needs in a developing country.

Complexity and Evolutionary Thinking From the field Process and Change Facilitation Sustainable Economic Development

The benefits of being aware of how a system works

For those that have participated in any of the training events that I have contributed to in the last years would hopefully recall my favorite energizer called the Systems Game. In this game we simulate a complex system, with all the participants moving around trying to position themselves between two targets in the group, without the targets being aware who is chasing them. Things usually start of neat and tidy, but soon chaos breaks out.  After the game we reflect on the system and how to better understand its behavior, and also how to figure out how to stimulate change of behavior in the system.

The pictures below were taken in the last Mesopartner International Summer Academy on Economic Development.

The participants secretly determine who they will follow
The participants tries to become system aware – who is following me?

One of the first insights is that our job as practitioners is not to try and fix the system, nor to solve a problem on behalf of the system. Our first job is to try and get the system to become more aware of its own behaviors, issues and dilemmas. Very often this will allow us to use some of the existing relationships, routines and networks of the system to improve the performance or to address some issues in the system.

I received the following little e-mail story recently that actually shows how actors that are aware of the system can easier manipulate the system to achieve certain outcomes. From a few google searches I could not determine the source of the story, except to see that its been featured in many fora. Therefere if you know the original source then please let me know so that I can give proper credit.

Here is the story as I received in my e-mail:

An old man wanted to plant a tomato garden, but it was difficult work, as the ground was hard.

His only son, Vincent, who used to help him, was in prison, and so the old man wrote a letter to his son:
Dear Vincent,
I am feeling sad because I won’t be able to plant my tomato garden this year. I’m too old already.
I know if you were here,  you would happily dig the plot for me, like in the old days.

A few days later, he received a letter from his son.
Dear Papa,
Don’t dig up that garden. That’s where the bodies are buried.
Love, Vinnie

At 4 am the next morning, FBI agents and police arrived and dug up the entire area without finding any bodies.
They apologised to the old man and left.

That day, he received another letter from his son:

Dear Papa,
Go ahead and plant the tomatoes now. That’s the best I could do under the circumstances.
Love, Vinnie

Now the moral of this story is that only people that are aware of how a system might behave can fully exploit the system to their advantage. I wonder how we can use this insight to promote better inclusiveness in development? From my everyday work experience I know that in value chains and production systems the poor, weak, small and marginalized are often the least aware of how the bigger system(s) around them work. The powerful, better informed and more successful entrepreneurs often have better information at their disposal. While some of this information could be formal, quite a bit of it is qualitative based on a deeper understanding of how things (might) work.

Addressing persistent market failure Sustainable Economic Development

Why the theories underlying economic development matters

I have been accused on several occasions of being too theoretical in my training approaches. These comments typically come from highly experienced development consultants and not from the target groups of my training, namely government officials, development facilitators and experts based within developmental organizations. I am not denying that I like to raise some more nerdy-like topics during my training, but this is based on my belief that you cannot be a developmental practitioner without understanding what the deeper knowledge bases are that we are working with.

I am always amused by this negative attitude towards of theoretical bases, especially when these consultants themselves start blurring the lines between the bases that they work from and the outcomes that they prefer.

Why do theories matter?

Bodies of knowledge, or theoretical basis are useful to development practitioners and are not only the domain of clever academics. Not only does a body of knowledge or theory provide us with some guiding principles, it also provides us with lines of inquiry or research questions. A theory also provides a boundary which typically explains what a theory does not cover. You could say that each theoretical base has its strengths (which means that it can structure, explain or questions certain phenomena) and its limitations (which means it does not provide structure, explanations or questions for other phenomena). So the main point is that a theory gives a development practitioner guidance as to what a theoretical base can inquiry, what questions it can find answers to, and which topics it does not provide much insight into. The main function thus of a theory is it helps us structure questions so that we can develop robust answers.

The importance of questions in development practice

Very often we find that developmental practitioners have posed very weak or generic questions at the start of a project or intervention. For instance, the question “how can we help the poor in this region?” is a poorly defined question as you will not be able to deal with the hundreds of answers ranging from “they must do it for themselves” all the way to “we must do it for them“.

Einstein is quoted as saying “if I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper question to ask, for once I know the proper question, I could solve the problem in less than 5 minutes“.

So we have to ask more specific questions that lead to more precise questions. These questions are shaped by our theoretical bases. For instance, someone from an engineering background (using an engineering base) will ask that question slightly differently than someone from a business background (using business management) or a social worker (using certain social subjects).

The result of blurring the lines between theories is that questions becomes blurred, leading to vague answers. When questions becomes blurred by experienced consultants, manipulation may occur.  This can be achieved by sequencing questions in a way that people (beneficiaries, donors, organizations, political interests) are lead into one or two “solutions” or conclusions. These conclusions, recommendations, or solutions (call it what you will) are also sometimes known as “magic bullets” or recipes for success. We all know that magic bullets are blind, because they are so dependent on a specific context or the experience of the expert advising them.

You should never trust the answer of a research study or report if you do not understand which questions were asked to guide the study. Despite the content of the research, the questions gives an important hint as to which theoretical bases where used, which also provides us with a clue to the limitations (or blindspots) of that theory.

I am not arguing that we cannot combine theories, rather, I am arguing that we should always remember which theories we are combining in our work. For example, if you are promoting value chains and you are not basing your questions on business management theories (including production, industrial, strategic and other forms of management), then on what bases are you relying for your questions? Are you depending on gut feel, past experience, anecdotal experience, ideology or personal value systems? Or even worse, do you see value chain promotion as an answer to an unasked question? (What was that question again?). And let us say you are depending on the example I provided of business management as a basis for value chain promotion, then what are you blind to because of the choice of theory? Business management theories provide very little insight into social issues, market functioning (not to be confused with marketing management) poverty alleviation, or more technical or scientific issues that you are typically confronted with when working with value chains in a developmental context. I could have of course used another example, but this is one that I am frequently confronted with.

Perhaps it is worth your while to reflect for a few moments on which bases you draw when you come up with recommendations or are confronted by a specific problem. You will be surprised to find that there are many other bases that will provide you with different questions that you might want to consider reading up on. Perhaps you will even find some explanations why some of your favourite viewpoints seems to be so vulnerable or prone to failure within certain contexts, or why people resist some of your ideas. Let me know what you find!!