Local economic development from a systems perspective
29 October 2010
Local economic development (LED) projects are being undertaken in many municipal areas of South Africa. These municipalities have been criticised by analysts for prioritising infrastructure and service backlogs above LED. Applying thinking in terms of system dynamics, Bodhanya shows that the municipalities are right, and that infrastructure and service delivery should be considered part of local economic development.
Systems thinking has permeated many sectors, including international development, since the publication of The Fifth Discipline: The Art and Practice of the Learning Organization (1990) by Peter Senge. While systems thinking focuses on inter-relationships between parts of a system, and the cause–effect relationships among them, it is assumed that systems thinking can help practitioners understand the context in which they work. But within any system there are a myriad of inter-relationships and nonlinear systems interactions, so that the context is often very difficult to comprehend. For practitioners, the question then arises: ‘how are we to intervene if it is so hard to understand the dynamics of these complex systems?’
In this article I will show that both systems thinking and complexity theory offer possibilities for concrete action. While complex systems may behave unpredictably, the good news is that it is patterned behaviour. While we may not be able to predict the weather with any precision in Jakarta in December, we know that it won’t be snowing. The behaviour of the weather system is unpredictable, but bounded. Systems thinking draws on this notion of unpredictable but patterned behaviour in the formulation of system archetypes. These are common templates and general patterns of behaviour that replicate in different domains and contexts. They serve as a starting point for understanding the complexity of a system, and for identifying points of intervention and leverage, while taking cognisance of the specific context.
In the following I will work out an example of an archetype called ‘Growth and Underdevelopment’, which is applicable to many of the local economic development (LED) projects being undertaken in many municipal areas of South Africa. The municipalities are often criticised by analysts for prioritising infrastructure and service backlogs above local development. Yet this thought experiment using systems thinking indicates that the municipalities are right, and that infrastructure and service delivery should be considered part of LED.
It is important to understand the basic convention when reading the systems archetype diagram. As explained below, the arrows represent relationships between factors. A change in one factor leads to a change in the corresponding factor at the head of the arrow.
The symbol ‘s’ means that the factors change in the same direction. If the perceived need to invest increases, then investment in capacity also increases. If, on the other hand, the perceived need to invest decreases, then investment in capacity also decreases. They move in the same direction.
The symbol ‘o’ means that the factors change in the opposite direction. If the service delivery backlog increases, then the level of demand decreases. If, on the other hand, the service delivery backlog decreases, then demand increases. They move in the opposite direction.
In the diagram below an increase in
investment in capacity results in an increase in
capacity, as indicated by the arrow to
capacity. This will happen after a period of delay, as building capacity takes
time and cannot occur instantaneously. The same logic is applied to all other relationships. A
combination of relationships results in feedback loops. The snowball icon refers to a positive
feedback loop, which means that an increase in a factor results in a further increase in that
factor as the relationships in the loop are followed. The diagram indicates that an increase in
demand leads to an increase in
growth, which leads to a further increase in
demand, and hence R1 is a positive feedback or reinforcing loop. The see-saw icon
refers to a negative feedback or balancing loop. As the
demand goes up it faces a limit in the form of a capacity constraint, called
impact of limiting factor, to service that level of demand. This has a negative
effect as it reduces
demand, shown by the symbol ‘o’. Therefore B1 is a balancing loop.

In the diagram, an increase in the impact of limiting factor leads to an increase in the perceived need to invest, resulting in investment that builds capacity, which reduces the impact of the limiting factor, thereby balancing the initial change. Therefore B2 is a balancing loop.
The Growth and Underdevelopment archetype has three feedback loops. These feedback relationships mean that while there may be growth, that growth will be undermined unless there is adequate capacity to service it adequately.
Once the development practitioner recognises the generic pattern of behaviour that is encapsulated in the archetype, (s)he can apply it by taking the specific development context and related dynamics into account in a specific setting. This is illustrated in the following example.
The generic archetype may be applied in the case of LED by drawing on some of the systemic relationships among the various attributes, as shown in the diagram below.
This indicates that while a locality may stimulate economic growth through, for example, encouraging the start-up of new enterprises, that growth could be short-lived and self-limiting if the increased demand for products and services is not met with increased capacity to satisfy the demand. Such increased capacity could refer to the road infrastructure to support the transport logistics for these enterprises, for example, or the water, sanitation and electricity infrastructure in a newly developed business park.
An increase in infrastructure reduces the service delivery backlog.
There are two new positive feedback loops, R2 and R3, both of which are triggered by the investment loop. An increase in infrastructure contributes to business growth directly, as well as indirectly through an improvement in service delivery. The problem is that the feedback loops also work in reverse. An ailing infrastructure and poor service delivery trigger the feedback loops that are in effect death spirals, and lead to the economic decline of a locality. A more perverse effect is that one of the key drivers is the standards of service delivery. In some cases, as a result of long periods of poor performance, there is the phenomenon of eroding goals, which leads certain actors to reduce their standards of service delivery. This is in turn accelerates the decline.
Two important lessons can be drawn from the foregoing analysis:
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Many of the districts and local municipalities where analyses such as this have been applied are characterised by poor infrastructure and massive service delivery backlogs, and hence are susceptible to Growth and underdevelopment. Any attempt to stimulate LED will be self-limiting within the capacity constraints.
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There is a systemic relationship between infrastructure and service delivery, and economic growth, so that LED must not be treated separately. Some analysts have criticised South African municipalities for prioritising infrastructure and service backlogs above LED. Such criticism is misplaced; the focus on improving infrastructure and service delivery is also part of local economic development.
Further reading
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Bodhanya, S. (2005) Strategy making: traversing complexity and turbulence. Paper presented at the 7th International Conference on Foresight Management in Corporations and Public Organizations: New Visions for Sustainability, Helsinki, Finland.
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Braun, W. (2002) The System Archetypes. View PDF
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Chapman, J. (2002) Complex adaptive systems. In System Failure: Why Governments Must Learn to Think Differently (2nd edn). London: Demos. ch.8, pp.51–63.
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Cilliers, P. (2000) What can we learn from a theory of complexity? Emergence, 2(1): 23–33.
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Levy, D.L. (2000) Applications and limitations of complexity theory in organization theory and strategy. In J. Rabin, G.J. Miller and W.B. Hildreth (eds), Handbook of Strategic Management. New York: Marcel Dekker.
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Meadows, D. (1999) Leverage Points: Places to Intervene in a System, Sustainability Institute, pp.1–19.
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Ormerod, P. (1998) Butterfly Economics: A New General Theory of Social and Economic Behaviour. London: Faber and Faber.
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Senge, P.M. (2006) The Fifth Discipline: The Art and Practice of the Learning Organization. London: Random House.
Other resources and interactive simulations
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Bodhanya, S. and Gerwel, C. (2009) Exploring the use of simulation as a tool of change management. Paper to be presented at the 3rd European Conference on Games-Based Learning, Graz, Austria, October 2009.
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Bots, P. and van Daalen, E. (2007) Functional design of games to support natural resource management policy development. Simulation and Gaming, 38(4): 512–532.
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Meadows, D. (2007) A brief and incomplete history of operational gaming in system dynamics. System Dynamics Review, 23(2–3): 199–203.
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Ruohomaki, V. (2003) Simulation gaming for organizational development. Simulation and Gaming, 34(4): 531–549.






