Yesterday, I had a discussion with a friend about the question whether any form of targeting of our interventions towards a specific group of people or topic is already limiting our ability to come up with solutions that are fully adapted to the system. The concrete issues we were talking about were the poverty orientation of the development sector in general and as an example the focus on women economic empowerment as a form of development in particular. The hypothesis we had is basically that if we enter a system with predefined clients (e.g. ‘the poor’ or ‘poor women’) in the first place, our solution will always by biased in order to directly and quickly cater those clients’ needs. This argument goes into the direction of the silo thesis, i.e., that development organizations basically have their topics, such as human health, water and sanitation, markets, etc., and that, regardless of the system or problem they encounter, their solution always has something to do with their topic.
In contrast to that, systems theory tells us that we need to take a holistic view on the system and not limit ourselves to one specific domain if we want to really understand how a system works. So if we only look at the problem of how women get their water and come up with the solution of digging a well in each village, we might miss the whole actual problem women are facing. As a consequence, the entry point for us to support the women might be somewhere completely else, for example local governments, traditional structures, etc.
Then again, what we as development practitioners want to achieve – be it in the short or the long run – is to reduce poverty and also to improve the situation of women, which, in many instances, suffer an even more dire fate as their male counterparts. Not to talk about the incentive structure of the funding of international development which clearly favors quick wins with specific target groups.
I did some more thinking on the topic and I guess the important differentiation we need to make is between what we look at during the system analysis and what we define as target state of the system. In the first, i.e., the system analysis, we have to be open and holistic and take into account all kinds of influences. The only thing we need to do is to set the appropriate system boundaries to frame the system and the level of aggregation that is useful for our work. But only once we have analyzed the system, we should hone in on our target variables, e.g., the poverty or the economic empowerment of women and see how we can influence the system so these variables change in a way that seems favorable to us.
Hence, holism and targeted interventions don’t have to be a trade-off per se. The trade-off, in my view, starts when we are designing the interventions. At that point we have to choose between interventions that have a short-term effect on our target variables or we have to appreciate the dynamics of the system and choose interventions that work with the system. The latter often have the price tag of only showing results after longer periods of time – although that is not necessarily always the case.
I’m curious about your thoughts on this topic and whether it makes sense what I am writing here.
Interesting. I would tend to agree with what you are saying, I think, but with a caveat.
An example in my language: say you are trying to facilitate fundamental change in a market system. The vision you have for the changed system might cover a number of factors (variables) that are important: for example (1) you want the system to be more competitive as a whole (competitiveness of the system), (2) you want the participation of traditionally marginalised people in the system to be improved, in absolute numbers participating and in terms of the benefits they derive from the system (call this inclusion of the system), and finally (3) you want the participation of these traditionally marginalised people to be more self-determined/empowered (called this, for lack of a better word, equitability of the system).
Practically speaking in most cases there are trade-offs that have to happen between factors (at the time of initial inception, and at every point when the facilitators reflect on how the system is changing and re-adjust their strategies of facilitation). In particular, if you are poverty-oriented then you may think it is important to trade off some competitiveness for greater inclusion or equitability.
Yes, at the point of mapping the market system (system analysis) we might not put a special emphasis on understanding the marginalised actors within it, (although where you set the boundaries impacts what you call marginalised actors and what are excluded actors). But when you build (to start) and rebuild (as you go along) the vision (the target state) I think that it is essential to have a very deep understanding of the marginalisation (in all its complexity) in order to make an informed judgements about balancing the different factors. Otherwise your judgements may turn out to be misguided as you strike the wrong balance because you don’t understand the marginalisation well enough.
So to me there’s a point between system analysis and target state definition that requires concerted focus on those who are marginalised if the target state is to involve a target to reduce the marganalisation variable.
Alexis, thanks a lot for your comment. I guess we do think along the same lines. You hit the point when you describe the three different goals that we want to reach. I guess the question there really is how – by keeping true to all three goals – you make this trade off to achieve a sustainable and long-term change or if these three goals are – at least in the short term, i.e., in the life time of a project – mutually exclusive in the first place.
My argument wants to stress the necessity of having a clear hypothesis on how the system works by conducting a thorough system analysis and, based on that, a theory of change on how to reach the desired target state. What I meant by setting the system boundaries and aggregation level of the analysis basically covers what you mention regarding the deep understanding we need to have on the aspect of marginalization in the system. But this understanding has to be systemic and not biased by topic-silos (e.g. marginalization of women in markets might be rooted in the social system).
Once we have our hypothesis on how the system works and once we work on the theory of change, we can judge on whether it is possible to reach all three goals and if not if they are mutually exclusive or what kind of trade-off we are facing.
Dear Marcus,
At a conceptual level you are right, there need not be a contradiction between the diagnosis and the intervention. But there are some challenges that systems theories introduce namely feedback loops, the time dynamic and also unintended consequences. Then there is the unsystemic insistence of donors that their specific target groups should “definitely” benefit, if not benefit disproportionally…… In the short term. In the worse case the donor or host tells you to focus your diagnosis and your interventions at your target group, thus confusing the target group (the actors that can best affect a change in the system) with the beneficiary group (the people we want to benefit from our interventions).
Coming back to the feedback loops. I have in recent years often witnessed how there are positive feedback loops that sometimes gives momentum to our interventions. Perhaps we were even in some cases smart enough to recognize some positive or reinforcing loops that we could then support to strengthen change in a certain direction. But there are also negative loops that naturally slows down a system. And these are often ignored. For instance, a societies willingness to relinquish power to women, or certain laws or traditions are often feedback loops that slows down change. Many donors are very nervous (rightly so) to address these issues.
The third dimension is time, and it is dynamic. Here in South Africa, there is the fear that a particular group other than the intended beneficiaries would benefit in the short term, therefore paralysis ensues. Rather do nothing than tip the scale in favor of the wrong group. But this time dynamic also have a longer term dimension. Sometimes the change will happen, it will just take much longer. Or it may happen over time because some other conditions are met. Or maybe it almost happens, but because on or two factors are weak the system reverts to an earlier state. We have to remember that in most systems theories there is a recognition of the importance of the starting state of the system AND the timing of the change.
Lastly, I have referred many times to change. Often we want systems to change, because we can see how a system is behaving in a sub-optimal way (take for instance gender, or environment). And sometimes the stakeholders in the system will agree with parts of our assessment, but they might actually connect things differently (with different weightings) than we do. But many programmes still try to change a system beyond the recognition and scope of the systems ability in the short term. This is where a lot of harm is done. We forget that the system must be ready for change, and then it must be ready for change in the extremes.
Just a few ideas from my side.
As we have often discussed in other platforms, I believe that the development field cause and effect even in its simplest forms are ignored, relationships between causes and effects under estimated, and the importance of time (especially in the longer term) are neglected. And then there are those loops….
Hi Shawn and Alexis. Thank you for your comments. I took some of your comments up and wrote a new blog article. I’m interested to your reaction to that. Please feel free to add comments to the new article.