Child pages
  • Governance system analysis
Skip to end of metadata
Go to start of metadata


Some insights from a theoretical perspective

A system can be defined a set of entities and a set of relations between the entities (Kramer and De Smit, 1997). Ideas about the nature and workings of phenomena as systems date back to the 17th century (Gerrits, 2008). Since that time, multiple variants of systemic theories have been developed and many of these are still evolving. The dominant systems theory originates in the 1950s and is rooted in many domains such as cybernetics and catastrophe theory but has also found its way into, among others, business administration and economics (Gerrits, 2008). However a number of assumptions of the first versions of general systems theory or total systems theory hampered a successful adaptation in both science and policy making. First of all, it treated all systems more or less equally, regardless of whether it concerned physical systems, social systems or psychic systems. Secondly, it assumed systems to be clearly recognizable and, thirdly, it assumed that systems have clear boundaries, i.e. stable demarcation in causation within systems. Soft systems methodology (Checkland, 1981) provided an alternative with the introduction of the learning human agent in systems instead of treating systems as disentangled from these agents (Flood, 1999). That important inclusion meant that systems where not treated as being separated from human perception and ideas about the nature of the system. Consequently, the idea that systems could be disentangled was abandoned and replaced by a more nuanced vision that acknowledged the cognitive and normative limits of human comprehension of systems. The focus shifted from the question how to achieve something in systems incontestably to what should be achieved (Otter, 2000). Understanding a system is therefore much a matter of understanding how humans define the systems and how they attempt to make sense of the complex causation inherent to systems. There is therefore a fundamental difference between physical systems and social and psychic systems.


Systems theory recognizes that events are rooted in complex causation, a large number of variables that cause and influence a certain event. While much science is oriented towards finding the one variable that explains the occurrence or change of some phenomenon, systems theory focused on the contingency of an event, explaining that a host of variables together caused that event (Flood, 1999). This way of thinking meant a change in science. It offered a new perspective about how one could work to improve systems. Systems theory, and its many variants, improved understanding of the network-like structure of causality. It analyzed the occurrence of positive and negative feedback loops that could explain that causal relations do not always produce the same stable and predictable output. It showed that systemic change can be erratic. (Gerrits, 2008).


This is also confirmed by Hermans and Thissen (2009, p. 1) who point out that more or less in parallel to the development of public policy analysis as a discipline during the 1960s and early 1970s, policy scientists have been criticizing policy analysts for being too narrowly focused on means-end rationality, pointing out the key roles of other types of rationality (political, procedural) and other factors in policy making, such as power, personal relations, strategic behavior and strategic use of information[1]. The reason for this is also that the methodology policy analysts applied had its main roots in operations research (OR) and applied systems analysis (Walker, 2000). In the perception of policy scientists, policy making is a social process of and between actors, rather than a rational effort to search for the optimal solution given a fixed problem definition. While this view of policy making does not argue that traditional analysis is irrelevant, it emphasizes its limitations and partly explains why the products of analytic efforts have been used to a limited extent only (Shulock, 1999). In response to these challenges posed by the multi-actor character of policy making, policy analysts have come up with a variety of new approaches, including participatory and interactive styles of policy analysis (Mayer et al., 2004). The latter often draw on soft OR methods for problem structuring and participatory analysis, which typically combine process and content dimensions in problem solving (Eden and Ackermann, 2001). Regardless of the preferred mode or style, the work of policy analysts could benefit from an analytical reflection on the actors that play a role in the policy making realm. Consequently, policy analysts are increasingly interested in, and make increasing use of, methods such as different types of systems analysis that help them to get a better understanding of multi- actor policy processes. As part of Delta Governance we define systems analysis as the study of sets of interacting entities and it has proved to be a useful approach in many multidisciplinary fields. In the field of governance, system analysis can be applied to focus on the analysis of societal and institutional frameworks and relations between actors (stakeholder analysis). The analysis can be of a descriptive nature (e.g. overview of formal and informal relations) or can include more explanatory aspects (e.g. overview of the effects of power relations).

Experiences from practice

Deltares has executed a number of projects and initiatives concerning system analysis. In the overview some examples are given:

  1. Deltares has been using a framework of analysis for a number of decades, based on international project experience and mainly driven by Prof. ir. Eelco van Beek. Currently a new version of the framework is being constructed: The Deltares Integrated Planning Framework.
  2. Stakeholder mapping has been executed in a number of projects both internationally and nationally for example: Sand and Sediment allocation in the Markermeer-IJmeer area (in the context of the building with nature research program). Retrospectively the Stakeholder mapping had a positive influence on the Quick Scan and the other way around. The Stakeholder mapping had an important contribution in creating a ‘buzz’: stakeholders got acquainted with the activities of Building with Nature in the Markermeer-IJmeer area. The objective of the Stakeholder mapping was to contribute to the future programming of the research program in the case study area Markermeer/IJsselmeer by providing insight on:
    • The stakeholders with clear stakes in sand and sediment dislocations in the Markermeer/IJmeer area;
    • The objectives and interests of these stakeholders in relation to sand and sediment dislocations in the Markermeer-IJmeer area, including an indication of the size of the interests;
  3. Learning history Waalweelde: this project was more of a retrospective system analysis with the aim to reconstruct the decision-making process how the ‘Waalweelde’ initiatieve came into being and get insight in the perspectives, perceptions and thus to help organizations become better aware of their own learning and change efforts[2].
  4. Corporate Innovation Program RWS: Research on the obstacles for effective cooperation and innovation within infrastructure projects commissioned by the Dutch Ministry of Infrastructure and the Environment; experienced by the three main stakeholders of the “golden triangle”: public client, market players (contractors and engineering consultants) and research institutes. A system analysis of the cooperation structure between these three parties was carried out based on a number of interviews. A number of causal loop diagrams portraying the main mechanisms of the system were built in order to discover the most important leverage points for effective innovation and on this basis propose a number of changes and boundary conditions needed to promote a faster adoption of innovative technologies in the sector.
  5. Building with Nature (BwN) Singapore: The general aim of the project is “to facilitate embedding of BwN ideas, developments and Eco Dynamic Design (EDD) in the decision making process on - and management of marine infrastructure”. More specific the aim is to identify how the decision making process for dredging in Singapore works. Within this process, identify the process around environmental criteria for dredging in Singapore. This information is to be used in the development of criteria for ecological relevant adaptive dredging near sensitive ecosystems. Secondly, the objective is to identify opportunities, constraints and recommendations resulting from the governance system for bio-diverse coastal protection in Singapore. Finally, the project aims to facilitate awareness and acceptance of BwN philosophy and eco-dynamic designing (EDD) with stakeholders in the coastal zone by co-producing knowledge and the facilitation of sharing knowledge.



[1] According to Laswell (1971): Policy science is about the production and application of knowledge of and in policy. Policy analysis according to Dunn (1994) is “an applied social science discipline that uses multiple research methods in a context of argumentation, public debate in order to create, critically evaluate, and communicate policy-relevant knowledge”.

[2] http://www.innoverenmetwater.nl/upload/documents/nieuw/leergeschiedwaalweelde/T2466_01.pdf

  • No labels