by Eva Shiffer

How can development projects achieve results in situations where there are many moving pieces, where the organizational structures and incentives may be stacked against effectiveness and at the same time, informal relationships and politics influence the result? Will it be enough to apply international best practice, adapted to the local context? Shall we present a menu of good practices and let the experts pick which one to apply where? What is the role of experimentation and feedback? How can we overcome the “analysis paralysis” that can easily overcome us when working in systems that are too complex or too chaotic to understand?

Complexity science provides some distinctions that make it easier to understand what kind of problem we are facing and what kind of solution or intervention is appropriate. Broadly, they distinguish between obvious, complicated, complex and chaotic systems.

Obvious systems work like a candy machine: One cause is clearly and explicitly linked to one effect, you put money in the slot, pull a lever and candy comes out. In international development, we want the customer experience in many public services to work like a simple system. The citizen fills in a form, fulfils explicit requirements, pays a fee and gets a permit. For obvious systems, international best practice is a good yard stick.

Complicated systems work like a car: They also have clear connections between causes and effects. However, they have so many interlinked chains of cause and effect that expertise is required to understand and change it. When something is broken in a car, a car mechanic can use their expertise to figure out what it is and repair it. As long as the car mechanic has a high level of expertise, they can identify and fix the problem. In international development, large and technologically advanced infrastructure projects are typical complicated systems. Challenges in complicated systems often have more than one solution. Experts can pick from numerous international good practices, and use their technical knowledge to adapt them to the local context.

Complex systems work like a family: While you can see family members strive, struggle and succeed, it is impossible to track down individual causalities, because whatever happens is caused by a whole range of interconnected reasons and reinforced or moderated by interlinking feedback loops. When working in complex systems the most powerful approach is to probe the system and see what happens: Implementing small experimental interventions, informed by technical and process knowledge to see how the system reacts. In this approach, it is important to act, observe, and adapt, reinforcing and scaling those interventions that were successful, changing those that were not and involving the members of the system in design, implementation, observation and adjustment.

Chaotic systems are like the immediate aftermath of 9/11: many things were going on at the same time and for any observer it was unclear how things were connected, what kind of system this was. The most important thing when working in a system that appears chaotic is to not freeze but take action – even without fully knowing the implications or understanding causalities - to provoke the system to reveal itself, because eventually the system will show characteristics of a complex, complicated or obvious system and then the above strategies can be applied. In international development, we are often plunged into chaotic systems in fragile states, when seemingly stable situations collapse unexpectedly.

Many projects we implement at the World Bank deal with a combination of obvious, complicated and complex (and sometimes chaotic) issues. Identifying which kind of system we are targeting with a specific set of interventions can enable us to know where we should bring in international best practice (obvious system), expertise and international good practices (complicated systems), experimentation and process facilitation (complex systems) or courage (chaotic system).

The work of the Collaborative Leadership for Development Program typically focuses on facilitating progress in complex systems. We perform analytical work to deepen our understanding of complex dynamics, design and implement interventions that engage members of the system with on-the-ground experimentation and adaptation to achieve results in those situations where cause and effect are not as simple to determine and technical expertise alone is not enough.

The thinking in this piece is based on the work of Dave Snowden http://cognitive-edge.com/ and others.