Taking responsibility for complexity (section 2.1): When is a problem complex?
This article is section 2.1 of a series of articles featuring the ODI Working Paper Taking responsibility for complexity: How implementation can achieve results in the face of complex problems.
Complex problems and the challenges they pose. This section [Section 2] should enable the reader to assess whether their implementation challenge is in fact a ‘complex’ problem, and to identify key characteristics to mark out the appropriate tools for managing the type of complexity faced. It first describes what is meant by a complex problem, and then outlines three specific aspects of complex problems that cause problems for traditional policy implementation. It goes into detail on each of these aspects, providing explanations and ideas to help the reader identify whether their policy or programme is complex in this way (Sections 2.3-2.5).
2.1 When is a problem complex?
The fact that some problems and issues are complex has been acknowledged for some time (both tacitly and explicitly), but in recent times complexity has been discussed with increasing frequency and sophistication. Complexity theory and the complexity sciences have attempted to investigate the integral characteristics of complex systems, investigating through theory and empirical research the ways in which interconnected, unpredictable phenomena work. A previous ODI working paper outlines 10 important characteristics of complex problems, relating in particular to features of systems that can be described as complex, the nature of change in complex systems and the role of agency in complex systems (see Box 1).
Box 1: Key concepts of complexity theory
Complexity and systems – These first three concepts relate to the features of systems that can be described as complex:
- Systems characterised by interconnected and interdependent elements and dimensions are a key starting point for understanding complexity science.
- Feedback processes crucially shape how change happens within a complex system.
- Emergence describes how the behaviour of systems emerges – often unpredictably – from the interaction of the parts, such that the whole is different to the sum of the parts.
Complexity and change – The next four concepts relate to phenomena through which complexity manifests itself:
- Within complex systems, relationships between dimensions are frequently nonlinear, i.e., when change happens, it is frequently disproportionate and unpredictable.
- Sensitivity to initial conditions highlights how small differences in the initial state of a system can lead to massive differences later; butterfly effects and bifurcations are two ways in which complex systems can change drastically over time.
- Phase space helps to build a picture of the dimensions of a system, and how they change over time. This enables understanding of how systems move and evolve over time.
- Chaos and edge of chaos describe the order underlying the seemingly random behaviours exhibited by certain complex systems.
Complexity and agency – The final three concepts relate to the notion of adaptive agents, and how their behaviours are manifested in complex systems:
- Adaptive agents react to the system and to each other, leading to a number of phenomena.
- Self-organisation characterises a particular form of emergent property that can occur in systems of adaptive agents.
- Co-evolution describes how, within a system of adaptive agents, co-evolution occurs, such that the overall system and the agents within it evolve together, or co-evolve, over time.
Source: Ramalingam and Jones1.
If a system or problem displays some of these characteristics, this is a signal that it may be complex. It is also possible to come from the perspective of someone attempting to tackle a problem, based on the starting point that many policy issues may pose real challenges for anyone trying to contribute to real change, making it difficult to know where to begin any interventions, whether interventions will make a noticeable impact and even how to measure their success. There are many different characterisations of what makes a problem complex; rather than choosing one, we present a few alternatives below.
One way of marking out these sorts of problems is to distinguish between ‘simple,’ ‘complicated’ and ‘complex’ problems. Glouberman and Zimmerman2 illustrate this by comparing the problem of baking a cake, sending a rocket to the moon and raising a child. In order to bake a cake (a simple problem), it is easy to use a recipe to replicate a positive outcome, with no particular expertise required. Sending a rocket to the moon (a complicated problem), on the other hand, requires high degrees of expertise, and must be divided into a number of tasks for specialists (e.g. engines, fuel), who must be coordinated. Nevertheless, building one rocket improves the chances of the next one functioning well, and there is a reasonable certainty of outcome. When raising a child (a complex problem), however, every situation is unique; previous success is no guarantee of future success; and, while expertise may help, it is not necessary or sufficient.
Another way of conceptualising complex problems comes from Ackoff3, who distinguished ‘puzzles’ and ‘problems’ from ‘messes.’ Puzzles have a well-defined, agreed statement of the problem, with solutions that can be tried and then abandoned or transferred to other similar problems. A problem has some agreeable structure, with known dimensions and variables, and has solutions that can be argued for depending on the particular constraints faced. A mess, however, does not have a well-defined form or structure, and there is little consensus on the most crucial aspects of the issue, let alone what goals to work towards. Messes tend to have a variety of dimensions (e.g. economic, technological, ethical, political), which are hard to separate from each other.
This is similar to the concept of a ‘wicked problem’ 4,5. Here, every problem is novel and unique, and there are no common ‘classes’ of solution. The parameters for solutions are incomplete, changing and often contradictory requirements which are often very difficult to recognise. The problem cannot be understood until a solution has been attempted, but the very effort alters the understanding of the problem and may reveal or create other problems. There is also no obvious test of whether a solution has been found, or whether a solution is ‘right’ or ‘wrong.’
Next part (section 2.2): Why does complexity matter in implementing policies and programmes?
See also these related series:
- Exploring the science of complexity
- Planning and strategy development in the face of complexity
- Managing in the face of complexity.
Article source: Jones, H. (2011). Taking responsibility for complexity: How implementation can achieve results in the face of complex problems. Overseas Development Institute (ODI) Working Paper 330. London: ODI. (https://www.odi.org/sites/odi.org.uk/files/odi-assets/publications-opinion-files/6485.pdf). Republished under CC BY-NC-ND 4.0 in accordance with the Terms and conditions of the ODI website.
References:
- Ramalingam, B. and Jones, H., with Reba, T. and Young, J. (2008). ‘Exploring the Science of Complexity: Ideas and Implications for Development and Humanitarian Work.’ Working Paper 285. London: ODI. ↩
- Glouberman, S. and Zimmerman, B. (2002). ‘Complicated and Complex Systems: What Would Successful Reform of Medicare Look Like?’ Discussion Paper 8. Ottawa: Commission on the Future of Healthcare in Canada. ↩
- Ackoff, R. (1974). Redesigning the Future: A Systems Approach to Societal Problems. New York: John Wiley and Sons. ↩
- Conklin, J. (2001). ‘Wicked problems and social complexity’, California: CogNexus Institute. ↩
- Rittel, H. and Webber, M. (1973). ‘Dilemmas in a General Theory of Planning’. Policy Sciences 4, Elsevier Scientific Publishing, Amsterdam, pp. 155-159. ↩
