In the last post I wrote about systemic change as the conditions or structures that hold a situation in place. I introduced the six conditions for systems change by Kania, Kramer and Senge and showed the little inverted triangle that puts the conditions in neat boxes and a clear hierarchy – the deeper ‘down’ the condition, the more influential over the system. I also introduced again the systems iceberg, which has a similar hierarchy and logic.
These two things – the neat boxes and the implied hierarchy – kept bugging me. I know that in complex systems things are never that neat and never linear causal – there is not one thing in one box that leads to another thing in another box or to an observed behaviour. Reality is messier. I also missed the dynamics in these diagrams – how are these structure created, how do they persist, how do they change? So I want to follow up on this in this post.
My company is a consulting firm and on my CV I call myself a consultant. Consultants are experts that are hired to bring solutions to a problem or improve the functioning of a mechanism, process or organisation. They are expected to have all the answers and are paid by somebody to give them the right answers to their questions or solutions for their problems.
When I work with organisations and teams on complex challenges, I often do not feel comfortable in this role as a consultant or expert. Too often, I do not know the answers or solutions. Too often, I have felt that moment of panic in the plane on the way to a client that I do not really know what to tell them, that I do not have the answers they are hoping to get from me. As I have said and written before, intervening in complex systems is not about fixing things, like fixing an engine. Complex systems are evolving interconnected systems. Understanding these interconnections and shifting the context is a more appropriate approach to change. This always needs to be based on a deep sense of understanding the local context and continuous mutual learning. Continue reading
I have never been very comfortable with the concept of root causes. I do see the need to go below the surface and not just look at the ‘symptoms’. Yet, it seems to me that the concept of root causes – one problem causing one or a number of symptoms – is at odds with the idea of complex systems, where patterns emerge as a result of a number of different interconnected and interdependent elements and structures.
The idea or root causes is linked to a linear cause-effect kind of thinking. This often plays out as follows: development agents going into a country, observing an undesirable pattern or symptom, doing some analysis to find a root cause, fixing it, and assuming the symptom will disappear – a linear causal chain is assumed from the root cause to the symptom. This is also the reason why many projects use results chains – chains of boxes and arrows indicating steps in a causal chain from the root cause to the symptom.
The problem with this type of thinking is that it does not reflect how the world really works. Still, this is how development generally approaches complex problems. Complexity thinking offers a different way of thinking about intractable or ‘messy’ issues such as getting stronger and more inclusive economies. One concept in particular seems helpful to replace the linear causal logic from root causes to symptoms: the concept of modulators. Continue reading