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Some problems are very persistent despite a lot of efforts by plenty of people to solve them. Examples are climate change, antibiotics over- and misuse, …. Persistent problems tent to be complex problems for which our traditional linear thinking recipes are ineffective. Einsteins quote “We can not solve our problems with the same level of thinking that created them” descibes this need to search for new and more appropriate ways to tackle these problems. Systems thinking is one of the lenses potentially providing clarity in complex problems. Other useful perspectives are complexity theory and design thinking.

A key understanding within systems thinking is that a system as a whole cannot be understood by analysis of its separate parts (M.Q. Patton 2015). The functions and meanings of the parts are lost when separated from the whole.



Meadows defines a system as “an interconnected set of elements that is coherently organized in a way that achieves something” (p. 11). Hence a system consists of three kinds of things: elements, interconnections, and a function or purpose. Elements are mostly visible tangible things, and are therefore the easiest to notice. You can divide elements into sub-elements and then in sub-sub-elements. Instead of intersecting elements, it is more interesting to look at the interconnections. The interconnections are the relationships that hold the elements together. If interconnections or purposes change, the systems behavior may alter drastically. Purposes are deduced from behavior, not from rhetoric or stated goals. Systems can be nested within systems. Therefore, there can be purposes within purposes. Sub-purposes can come into conflict with the overall purpose. Keeping sub-purposes and the overall system purposes aligned, is essential for a successful system (Meadows 2008).


BOX: Questions to ask in order to know whether you are looking at a system or just a bunch of stuff (reproduced from Meadows, D., 2008)

A)  Can you identify parts?        

B)  Do the parts affect each other?        

C)  Do the parts together produce an effect that is different from the effect of each part on its own?
AND perhaps

D)  Does the effect, the behavior over time, persist in a variety of circumstances?




Systems thinking is gaining popularity and becomes increasingly influential. Its origin goes back far in history. The International Institute for General Systems Studies (IIGSS) developed a family tree going back as far as 2500 years (see http://www.art-sciencefactory.com/complexity-map_feb09.html). The origin of systems thinking is spread out over many intellectual knowledge domains. In the recent 20 to 30 years systems thinking is applied in a fast growing number of knowledge domains (e.g. sustainability, weather forecasting, social problems, public health,…).


Systems thinking is closely linked to the paradigm of complexity. During the early 1950s a number of scientists (e.g. Ashby, Bertalanffy and Boulding, founders of the ‘systems-movement’), recognized the need for a trans-disciplinary approach in order to deal with growing complexity (Nys 2014). The idea was to develop a ‘general systems theory’ (von Bertalanffy 1956).

From the study of non-linear dynamic systems (e.g. weather patterns) a new family of systems theories appeared in the late 20th century, heavily nurtured by research at the Santa Fe Institute of Complexity (Nys 2014). A paradigm shift in scientific thinking developed with at its core the shift from an orientation towards equilibrium and statics towards a kind of thinking that is oriented towards disequilibrium, self-organization, non-linear dynamics, emergence and unpredictability (Nys 2014).

Kefalas (Kefalas 2011) formulated the following main characteristics of systems thinking:

  • Systems thinking is a view of the world: it is the conceptual schema by which one organizes one’s thoughts and actions with respect to reality;
  • Systems thinking is interdisciplinary. It attempts to build a general viewpoint by borrowing from many seemingly diverse disciplines which is a departure from conventional scientific thinking;

Systems thinking conceives real-world phenomena as systems and stresses interrelationships and interactions among the entities generating these activities rather than on the entities themselves.



Central to a systems perspective is holistic thinking, as opposite of reductionist thinking. A key understanding within systems thinking is that a system as a whole cannot be understood by analysis of its separate parts (M.Q. Patton 2015). The functions and meanings of the parts are lost when separated from the whole. Therefore a systems approach requires synthetic thinking, which is fundamentally different from analysis. To analyze is to explain by taking things apart in a first step, the contained parts are explained in a second step and finally knowledge of the parts is aggregated into knowledge of the whole. To synthesize is to see something as a part of a larger whole, next the containing whole is explained, and finally the understanding of the whole is disaggregated to explain the parts by revealing their role or function within that whole. Synthetic thinking reveals why a system works the way it does, but not how it does so. Analysis and synthesis are complementary and systems thinking incorporates both (M.Q. Patton 2015).

[To develop further]


At its broadest level, systems thinking encompasses a large and fairly amorphous body of methods, tools, and principles, all oriented to looking at the interrelatedness of forces, and seeing them as parts of a common process” (Senge et al. 1994)).


Systems thinking appears fragmented as it covers many different meanings, models, approaches and methodologies, including for example system dynamics, soft systems methodology and critical systems thinking (M. Q. Patton 1999). Therefore it is not surprising that systems thinking serves several purposes. Each “sub discipline” has its own objectives and represents a different way to approach complexity. System dynamics are appropriate when the aim is to clarify complexity and/or predict future behavior of a system, systems thinking reveals a variety of potential actions you may take to bring about change in a strategically desired direction. “Each of these actions will produce some desired results and (almost certainly) some unintended consequences somewhere else in the system. The art of systems thinking includes learning to recognize the ramifications and trade-offs of the action you choose” (Senge et al. 1994)

5.1 Soft Systems Methodology (SSM)

5.1.1 What is it about?


Checkland and Poulter defined SSM as follows:

“SSM is an organized way of tackling perceived problematical (social) situations. It is action oriented. It organizes thinking about such situations so that action to bring about improvement can be taken” (Checkland and Poulter 2010), p. xv).

SSM uses system ideas developed within hard systems thinking in problem solving. SSM is an approach which in a systematic way tries to establish and structure a debate concerning actions for improving the problem situation (Simonsen, 1994, http://www.jespersimonsen.dk/Downloads/SSM-IntroductionJS.pdf)(Simonsen 1994). Soft systems approaches diverge from hard systems approaches in explicitly integrating the assumption that an objective representation of reality does not exist. Our perspective is always directed and filtered by our world view. We always have only a partial picture of reality (See illustration).

Illustration: The blind men and the matter of the elephant (reproduced from Meadows, D., 2008, p. 7)

Beyond Ghor, there was a city. All its inhabitants were blind. A king with his entourage arrived nearby; he brought his army and camped in the desert. He had a mighty elephant, which he used to increase the people’s awe.

The populace became anxious to see the elephant, and some sightless from among this blind community ran like fools to find it.

As they did not even know the form or shape of the elephant, they groped sightlessly, gathering information by touching some part of it.

Each thought that he knew something, because he could feel a part…

The man whose hand had reached an ear… said: “It is a large, rough thing, wide and broad, like a rug.”

And the one who had felt the trunk said: “I have the real fact about it. It is like a straight and hollow pipe, awful and destructive.”

The one who had felt its feet and legs said: “It is mighty and firm, like a pillar.”

Each had felt one part out of many. Each had perceived it wrongly…

This ancient Sufi story was told to teach a simple lesson but one that we often ignore: The behavior of a system cannot be known just by knowing the elements of which the system is made.


Soft system methodology tries to align the partial pictures to be able to take coordinated action. This radical constructivist perspective includes that social systems do not exist as such, but are always informed by intentionality. Identifying this intentionality is at the core of SSM (Vandenbroeck 2015).

In short, SSM can be characterised by the following points:

  • In contrast to the approaches described above (grounded theory and framework analysis), SSM is an action-oriented approach, which means that its purpose is to enable actions to improve (Checkland, 2000, research paper)(Checkland 2000). The change sought can be structural change, process change or changes of attitude, or all three at once (Checkland, 2000, research paper)(Checkland 2000).
  • SSM is used “to make sense of complex situations” (Checkland, 2000, research paper)(Checkland 2000).
  • SSM is flexible. Any approach able to deal with the changing complexity of real life needs to be flexible, because every situation involving human beings is unique. SSM offers a set of principles which can be adopted and adapted for use in any real situation in which people want to take action to improve it. SSM is not a clear sequence of steps. (Checkland, 2000, research paper)(Checkland 2000)
  • SSM is a learning cycle, which goes from finding out about a problematical situation to defining/taking action to improve it. (Checkland, 2000, research paper)(Checkland 2000)

Checkland (Checkland and Poulter 2010) emphasized that SSM is not a technique in the sense of a recipe, nor a method, but a methodology. That means it is a set of principles which can be adapted for use in a way which suits the specific nature of each situation in which it is used. The set of principles can be adopted or adapted for use in any real situation in which people are intending to take action to improve it.


5.1.2 The SSM learning cycle


Adapted from Checkland and Poulter (2010)


The SSM process takes the form of a cycle. It is a cycle of learning which goes from finding out about a problematical situation to defining/taking action to improve it. The steps in the learning cycle are described below (see also Figure X).


Figure X: The SSM’s learning cycle


Real system

Soft  system world

2) Formulate root definitions

3) Build activity models

1) Find out about the problematical situation

4) Use the models to question the real world situation

5) Define actions to improve the situation Find out about the problematical situation


The starting point is a problematical situation. Problematical situations are characterized by:

  • Multiple interacting actors with each their own perception of reality or world view
  • People acting purposefully, with intention.

In the language of SSM four ways of finding out about a problematical situation are described.


a. Making rich pictures

Rich pictures are created to show multiple interacting relationships, hence illustrate the complexity of human situations. Knowledge about a situation can be assembled by means of interviews, reading documents, attending meetings etc. and be summarized afterwards in a rich picture. The pictures become richer as inquiry proceeds. In making a rich picture the aim is to capture, informally, the main entities, structures and viewpoints in the situation, the processes going on, the currently recognized issues and any potential ones. Qualitative research techniques (such as observations, interviews, focus groups) are particularly suited to build rich pictures.


b. Analyzing the intervention

Identify who are in the roles of ‘client’ and ‘practitioner’, and who could be included in the list of issue owner?

  • The client is the person or group of persons who caused the intervention to happen.
  • The practitioner is the person or group of persons who were conducting the investigation
  • Owner of an issue are people who are concerned about or affected by the situation and the outcome of the effort to improve it.


c. Analyzing the social

If we want to know whether a practical action could improve a situation, then the changes involved in ‘improvement’ have to be not only desirable but also culturally feasible. They need to be possible for particular people, with their particular history and their particular world views.

Three elements help to create the social texture of a human situation:

  • Roles or social positions differentiating between members of an organization. Some roles are formally recognized (e.g. director, department head, team member etc.) other roles are informal and linked to individuals’ reputation.
  • Norms are expected behaviors associated with a role.
  • Values are the standards by which role behavior gets judged.

Every time you interact with the situation by talking to people, reading documents, sitting in a meeting, conducting an interview, you learn about the roles, norms and values characterizing a particular group. Document them by writing down notes or memo’s.


d. Analyzing the political

The political is about the disposition of power in a situation and the processes for containing it. This is a powerful element in determining what is culturally feasible. Politics is also about accommodating different interests. In this analysis it is asked ‘how is power expressed in this situation?’ What are the commodities (e.g. personal charisma, membership of various committees, reputation, access to information, etc.) which signal that power is possessed in this situation? What are the processes, by which these commodities are obtained, used, protected, defended, passed on, relinquished, etc. Formulate root definitions


In order to construct an activity model, we need a statement describing the activity system to be modelled. This description is the root definition (RD), i.e. the description of what the system does, how and why. This is known as the PQR formula: do P (what), by Q (how), in order to help achieve R (why). The root definition is written out as a statement modelling a transformation process.


Although the PQR formula helps to define the root definition, which is the basis for the activity model, it can be further enriched by the use of the mnemonic CATWOE. The idea is that purposeful activity, defined by a transformation process (T) and a worldview (W) will require people (A) to do the activities which make up T. It will affect people (C) outside itself who are its beneficiaries or victims. It will take as given various constraints from the environment outside itself (E). It could be changed or stopped by persons (O) who are regarded as owning it.

  • C  customers
  • A  actors
  • T transformation
  • W  worldview
  • O owners
  • E  environmental constraints Build activity models


Building activity models means putting together the activities needed to describe the transforming process, in other words defining and linking the activities needed to achieve the transformation process. It is about the activities which do the transforming. Every phrase in the root definition should lead to something in the model, and every activity in the model must be linkable to something in the root definition.

The purposeful activity models can never be descriptions of (a part of) the real world. They model only one way of looking at reality, one world view. Activity models are devices which make sure that the learning process is not at random, but organized.

In addition to the root definition, it is useful to include control and monitoring activities by thinking about performance criteria, such as efficacy, (is the intended outcome produced?), efficiency (is the transformation achieved with a minimum use of resources) and effectiveness (does the transformation help achieve some higher-level or longer term aim?)

Activity models do not model the current ways of working but rather the concepts in the root definition. The aim is to question current practice by comparing the model to the real world situation.

It is useful to make models of purposeful activities whose boundaries cut across organizational boundaries, instead of accepting the organizational boundaries as a given. Purposeful activities are often institutionalized within departments, divisions, sections etc. Therefore it is tempting to model activities along internal organizational boundaries. Although this is not wrong, one should be conscious about the limitations this brings about. For example, organizational boundaries of departments are often linked to power play going on in organizations, because it is about allocating resources. To stimulate the (out of the box) thinking of the researchers it is useful to make models of purposeful activity cutting across organizational boundaries, hence independent of existing structures. You should not be modelling the current ways of working, but rather questioning current practice and build theoretical activity models, which are next compared to the real world. Also remember to stay focused on the root definition when building the model. Notice that the activity models do not purport to become accounts of what we would wish the real world to be like. They could not, since they are artificial devices based on a pure worldview, whereas human groups are always characterized by multiple conflicting worldviews (even within one individual) which themselves change over time.


The following steps could help you to build activity models:

1)     Assemble the guidelines: PQR, CATWOE etc.

2)     Write down three groups of activities – those which concern the thing which gets transformed, those activities which do the transforming, and any activities concerned with dealing with the transformed entity.

3)     Connect the activities by arrows which indicate the dependency of one activity upon another.

4)     Add the three monitoring and control activities.

5)     Check the model against the guidelines.  Does every phrase in the root definition lead to something in the model? Can every activity in the model be linked back to something in the root definition?

As a guideline, the operational part of the model could contain 7+/-2 activities. Using the models to question the real world situation


As already explained, the activity models are the devices or tools which enable that discussion is a structured rather than a random one. The models are sources of “good” questions to ask about the real situation, enabling it to be explored richly. For example: here is an activity in this model, does it exist in the real situation? Who does it? How? When? Who else could do it? The questions resulting from the comparison between the activity model(s) and the real world could be addressed in a focus group or even an individual face-to-face interview. An informal approach is to have a discussion about improving the situation in the presence of the models. If some relevant models are on flip charts on the wall, they can be referred to and brought into the discussion at appropriate moments. We could ask whether we would like activity in the situation to be more, or less, like that in the model. Such questioning organizes and structures a discussion/debate about the real world situation. The purpose of the discussion is to surface different worldviews and to seek possible ways of changing the problematical situation for the better.

Note that the models are not meant to be accounts of what we would wish the real world to be like. It is dangerous to talk about the comparison between the real situation and the models, because it can be taken to imply that the discussion focusses on deficiencies in the situation when set against the ‘perfect’ models. The models only reflect pure worldviews, which in real situations co-occur within the group or even within one person.

An activity model and the questions being raised out of the comparison between the model and the real situation, can be summarized in a matrix (type excel table) (see Table X). The model provides the left-and column, consisting of activities and connections from the model, while the other axis contains questions to ask about those elements. The task is then to fill in the matrix by answering the questions.

Table X: Example of a matrix template



Who does it?















 Define/take action to improve the situation, seek accommodation


Identifying different world views and seeking ways for improvement, means finding an accommodation, this is “a version of the situation which different people with different worldviews could nevertheless live with” (Checkland and Poulter 2010 p. 55). Checkland and Poulter (Checkland and Poulter 2010) explicitly differentiate accommodation from consensus. Consensus is static and suggests that everyone agrees about everything, while accommodation “emphasizes the provisional and even precarious character of an agreement between different interests and perspectives” (Vandenbroeck 2015). Accommodations involve compromise or some yielding of position. It is a necessary step in moving to deciding about what to do in a particular situation.

As discussion based on using models to question the problematical situation proceeds, worldviews will be surfaced, entrenched positions may shift, and possible accommodations may emerge. Any such accommodation will entail making changes to the situation, if it is to become less problematical, and discussion can begin to focus on finding some changes which are both arguably desirable and culturally feasible. In practical terms it is a good idea not to try and discuss the abstract idea ‘accommodation’ directly. It is best approached obliquely through considering what changes might be made in the situation and what consequences would follow. The practical way forward in seeking accommodation is by exploring possible changes and noting reactions to them” (Checkland and Poulter 2010) p. 58).

Change in real situations usually entails making changes to structures, processes or procedures, and attitudes. Structure is the easiest to change. But new structures usually require both new processes and new attitudes on the part of those carrying out the processes or being affected by them.


Questions which can inspire discussions leading to accommodation are:

  • What combination of structural, process and attitudinal change is needed?
  • Why?
  • How can it be achieved?
  • What enabling action is also required?
  • Who will take action?
  • When?
  • What criteria will judge
  •  success/lack of success
  • completion

These questions represent things to think about when considering changes which are both desirable and feasible. The question about “enabling action” refers to which actions are needed to make a potential change accepted. This recognises the social context in which any change is embedded. Because of this context, introducing the change may require enabling action, which is not directly part of the change itself.


Concluding remark:

Notice that the four stages of the SSM learning cycle should not be treated as a sequence of steps. “Although virtually all investigations will be initiated by finding out about the problematical situation, once SSM is being used, activity will go on simultaneously in more than one of the ‘steps’” (Checkland and Poulter 2010) p. 14).

5.2 System dynamics


System dynamics are a toolbox to model the dynamics of complex systems (Vandenbroeck 2015). System dynamic models are used in many different fields (e.g. climate change). Key to the system dynamics approach is that it understands the behavior of a system as the result of cause and effect relationships between parts of a system (Vandenbroeck 2015). Feedback and delays are the core mechanisms which enable simulation of complex non-linear dynamic systems’ behavior. Peter Senge applied system dynamics to bottlenecks in organisations (Senge et al. 1994).


In what follows we present tools to analyse a problematic situation from a systems thinking perspective. Some of them owe to system dynamics as used by Peter Senge (Senge 1990) to understand and elicit organizational change. The iceberg, reinforcing and balancing feedback loops are explained, archetypes are presented and Senge et al.’s seven steps for breaking through organizational gridlock are described. These tools are especially valuable to identify patterns and feedback processes and how they can generate (problematic) patterns of behavior within organizations or systems at large.

5.2.1 The iceberg model


The iceberg is a metaphor associated with systems thinking (Senge 1990). Systems thinking approaches problems by asking how various elements within a system influence one another. The visible world around us is represented by the top of the iceberg, but this is only a “manifestation of patterns and structures that are below the water surface, hence cannot be observed directly” (Vandenbroeck 2015). What happens under water is what creates the icebergs behavior at its top. The iceberg represents a hierarchy of levels of understanding with observable events at the top and mental models at the bottom.


  • Observable events

The guiding question to find out about events is: “What just happened?”. The response is the events resulting from system behaviour or repeating patterns of cause and effect at the lower layer of the iceberg.

  • Patterns/trends

Below the events level, patterns and trends become visible, by asking “What trends have there been over time?”. Similar events have been taking place over time.

  • Underlying structures

At the structure level we could ask: “What is causing the pattern we are observing?” or “What are the relationships between the parts?”. Structures might consist of physical things (like buildings, roads, etc.), organisations (e.g. schools), policies (e.g. laws) or rituals (e.g. habits).

  • Mental models

Mental models are the images, assumptions, and stories which we carry in our minds of ourselves, other people, institutions, and every aspect of the world. Like a pane of glass framing and subtly distorting our vision, mental models determine what we see” (Senge et al. 1994). Also “Differences between mental models explain why two people can observe the same event and describe it differently” (Senge et al. 1994). In qualitative research we encounter mental models often in (mis)beliefs, expectations, values and attitudes.

We are unaware of our mental models or those of others, until we diliberately look for them. By means of qualitative research, and especially in combination with a systems thinking or grounded theory approach, we can bring mental models to the surface and explore them. Once we identified them we can try to re-form mental models or create new ones that serve us better in the world. Soft systems methodology (but also for example imagineering) can help us doing this. Mental models are the deepest layer of the iceberg, which is suggesting that they are difficult to reach and unresponsive to change. However, if mental models can be changed they offer the highest leverage for change (e.g. within an organisation or system) (Senge et al., 1994).


The lower level of the iceberg gives context and meaning to the higher level” (Vandenbroeck 2015). For every event you can work your way down the iceberg through the patterns, underlying systems and mental models. It can also be useful to move up and down between levels as you think more about the event. The iceberg should help to broaden your perspective. Each layer offers opportunities to “enter” the system. New leverage points, these are points at which to intervene in a system to systematically transform it, may become apparent.


5.2.2 Reinforcing and balancing feedback loops


Adapted from Senge, P. et al. 1994, the fifth discipline field book, p. 113-120


In a feedback loop every element is both ‘cause’ and ‘effect’. For every variable you can trace links that represent influence on another element. This way cycles are revealed that repeat themselves. Figure X presents an example with increasing numbers of patients increasing waiting times in a clinic, and increasing waiting times leading to decreasing numbers of patients, leading to decreasing waiting times again, and so on.

Figure X: Example of a feedback loop


There are basically two building blocks of all systems representations:

  • Reinforcing loops: generate growth and collapse, in which the growth or collapse continues at an ever-increasing rate. A small change builds on itself, resulting in big changes after some time. There can be any number of elements in a reinforcing loop, all propelling each others’ growth. Reinforcing loop situations generally “snowball” into highly amplified growth or decline. Somewhere sometime the reinforcing loop will run up against at least one balancing mechanism that limits it. The letter R is used to mark a reinforcing loop.
  • Balancing loops: generate stability. Balancing processes generate the forces of resistance, which eventually limit growth. Balancing loops are found in situations which seem to be self-correcting and self-regulating. The letter B is used to mark a balancing loop.

In addition to feedback loops also time needs to be taken into account. Both in reinforcing and balancing loops delays may occur. Delays are the points where the link takes a particularly long time to play out. Delays can have enormous influence in a system, frequently accentuating the impact of other forces. When unacknowledged delays occur, people tent to react impatiently, usually redoubling their efforts to get what they want. This results in unnecessarily violent oscillations. One of the purposes of drawing systems diagrams is to flag the delays which you might otherwise miss. 


5.2.3 System Archetypes


Adapted from Senge, P. et al. 1994, the fifth discipline field book, p. 165-172


Archetypes are accessible tools with which credible and consistent hypotheses can be constructed. Kim and Lannon (Kim and Lannon 1997) rightly point out that they can be used in at least for different ways:

  • As “lenses”: it is not about which archetype is “right”, but rather about what unique insights each archetype offers.
  • As structural pattern templates: archetypes can help focus a group’s attention on the heart of an issue. After a group has drawn a causal loop diagram of the problem at hand, they can stand back and compare their diagram with the pattern of an archetype.
  • As dynamic scripts (or theories): each archetype offers prescriptions for effective action. Once we recognize a specific archetype at work, we can use the theory of that archetype to expel a particular problem and work toward an intervention.
  • As tools for predicting behavior: systems archetypes can help us identify predetermined outcomes of a particular situation.

To find out which archetype applies, a good strategy is to look at your situation through the lens of several different archetypes. Two or three may fit together, each highlighting a different aspect.

You can start by drawing just a simple balancing or reinforcing loop. Then add more elements, one link at a time. About each element ask what is causing changes in this element, and also what is the effect when this variable changes.

In what follows, three archetypes are presented. However many more archetypes are described in

  • Senge, P. et al. 1994, The fifth discipline field book, p. 125 – 150.
  • Meadows, D. 2008, Thinking in Systems. p. 110 – 141.     The “fixes that backfire” archetype

The central theme of this archetype is that almost any decision carries long-term and short-term consequences, and the two are often diametrically opposed. A problem symptom cries out for resolution. A solution is quickly implemented (the fix) which alleviates the symptom (balancing loop), but the unintended consequences of the fix (reinforcing loop) actually worsen the performance or condition which we are attempting to correct.

Example: child abuse is underreported to authorities. In the US they made reporting mandatory. However, child protection services were not reinforced, hence were overwhelmed by the number of reports, and could only investigate a small part of all reports. By consequence they got the reputation of being untrustworthy. In response, people decided not to report (although mandatory) and tried to find solutions themselves or did not do anything. Number of reports decreased again, hence the problem of underdetection was reinforced.


Figure X: System dynamics model for “Fixes that backfire” – example     The “Limits to growth” archetype

We never grow without limits. In every aspect of life, patterns of growth and limits come together. In this archetype the growth process is usually shown as a virtuous reinforcing loop. The limiting process is usually shown as a balancing loop, which reacts to imbalances imposed on it by the growth loop. The balancing loop is also driven to move toward its target – a limit or constraint on the whole system, difficult to see because it is so far removed from the growth process.

By pushing hard to overcome the constraints, we make the effects of those constraints even worse than they otherwise would be. Typically, there has been an acceleration of growth and performance, usually the result of hard work, but the growth mysteriously leveled off. A natural reaction is to increase efforts that worked so well before. However, the harder you push, the harder the system seems to push back. Some source of resistance prevents further improvements. Instead of the expected growth, performance remains in equilibrium or completely crashes.

The limiting force may be within the organization, within ourselves or it might be external (e.g. a saturated market).

Example: Quality improvements within an organization often start with the quick wins. This may lead to significant gains in the quality of services or processes. But as the easy changes (known as the low hanging fruit) are completed, the level of improvement plateaus. The next wave of improvements are more complex and tougher to make. The lack of organization-wide support may become a limiting factor.


Figure X: System dynamics model for “limits to growth” - example     The “Shifting the burden” archetype

A ‘shifting the burden’ situation (like a ‘fixes that backfire’ situation) usually begins with a problem symptom that prompts someone to solve it. The solution(s) relieve(s) the problem symptom quickly. However the solutions divert the attention away from the fundamental source of the problem.

The ‘shifting the burden’ model has two balancing loops, each representing a different type of fix for the problem symptom:

  • The upper loop is a symptomatic quick fix
  • The bottom loop represents measures which take longer (note the delay) and are often more difficult, but ultimately address the real problem.

In many ‘shifting the burden’ situations there are additional reinforcing loops. Like the “unintended consequences” loop in ‘fixes that backfire’, these loops represent unintended consequences that make the problem worse.

Example: Many cases of child abuse remain undetected (= problem symptom). An attempt to fix this underdetection could be to increase detection skills of general practitioners and pediatricians. However, if physicians detect more cases of child abuse, they often rely on child protection services for support, advice or to report the case. This means more work for the already overburdened protection services. They cannot manage the overwhelming demands of physicians and restrict uptake criteria or respond with ‘you are doing fine’. Physicians get discouraged and feel let down. As trying to handle cases of child abuse is very time and energy consuming, physicians go back to their former management of bruised children. A more fundamental solution would be to invest in the capacity of child protection services. This way physicians could get the support they need in the detection of child abuse and reported cases get the specialized care they need.


Figure X: System dynamics model for “shifting the burden” – example of the detection of child abuse     Links to other archetypes


5.2.4 Seven steps to break through organizational gridlock


Adapted from Senge, P. et al. 1994, the fifth discipline field book, p. 165-172.


Gridlock results when people behave as if they are independent, each pulling in a different direction.

Step 1: Identify the original problem symptom

Look back over a period of time and identify a class of symptoms that have been recurring.

Step 2: Map all quick fixes

Try to map out all the fixes that have been used to tackle the identified problem. The objective is to identify a set of balancing loops that appear to be keeping the problems under control.

Step 3: Identify undesirable impacts

Actions taken by one group almost always affect others in the organization (e.g. if each team’s solution causes a problem for the other team). Identify a reinforcing process that locks the players into a patterned response.

Step 4: Identify fundamental solutions

Having identified the undesirable effects of your quick fix, you need to find a solution that will more fundamentally address the problem. You will need to look at the situation from everyone’s perspective to achieve a fundamental solution.

Step 5: Map additive side effects of quick fixes

There are usually side effects of the quick fixes that steadily undermine the viability of the fundamental solution. This leads to a reinforcing spiral of dependency.

Step 6: Find interconnections between to fundamental loops

Finding links between the interaction effects and the fundamental solution. The interaction effects create spiraling resentment, which leads to an increasing unwillingness to communicate with the other team, resulting in an ‘us’ versus ‘them’ mentality.

Step 7: Identify high leverage actions

If you are able to get a bird’s eye-view, you can see the larger grid. The process of mapping out a gridlocked situation can be a high leverage action and be a starting point for communication across walls.

You know you found a high leverage intervention when you can see the long-term pattern of behavior shift qualitatively in a system, for example if stagnation gives way to growth or if oscillations dampen. This kind of breakthrough happens most readily when you can make alterations in the structure you’ve mapped out. You either add new desirable loops or break linkages that produce undesirable impacts.

  • Adding a loop: translates into designing and implementing a new process, monitoring information in a new way, or establishing new policies.
  • Breaking a link: eliminating or weakening undesirable consequences of your actions or ceasing strategies which are counterproductive in the long run.

When you add loops or break links, it’s critical to try to make such mental models explicit, because the reasons underlying peoples’ actions are fundamental to the system’s structure.




Systems thinking and qualitative research are a fruitful combination. Some approaches to systems thinking make use of qualitative inquiry and a systems orientation can be very helpful in making sense out of qualitative data (M.Q. Patton 2015).

Specifically for system dynamics Luna-Reyes and Andersen (2003)(Luna-Reyes and Lines Andersen 2003) posit: “The question for system dynamics appears not to be whether to use qualitative data but when and how to use it” (p. 274). There is qualitative modeling that goes through the process of formalizing and analyzing feedback loops but never results in the simulation of a mathematical system dynamics model. Qualitative methods can contribute to the conceptualization, formulation and assessment of these system dynamics models. Also soft systems methodology makes use of qualitative inquiry throughout its learning cycle, for example to make rich pictures of a problematical situation.

In addition, qualitative research and systems thinking are characterized by the same ontology and – at least for soft systems methodology - epistemology. Both take a non-reductionist and subjectivist position. Qualitative research is interpretive, meaning that qualitative researchers attempt to make sense of phenomena in terms of the meaning people bring to them (Denzin and Lincoln, 2000)(Denzin and Lincoln 2000). Qualitative researchers recognize that the subjectivity of the researcher is intimately involved in scientific research and they make subjectivity their strength, rather than their weakness. This constructivist approach is also key to soft systems methodology (see ADD CROSREFF). Typically qualitative researchers ask how and why questions (see the lower layers of the iceberg model, ADD CROSSREF) as opposed to what, who and where questions (referring to the upper layers of the iceberg model, ADD CROSSREF). Qualitative research is used when things are more complex and not reducible to closed answer categories.

Systems thinking is just another way of seeing, which also offers an alternative to the reductionist way of thinking. As with qualitative research, it is not a matter of which way is best. Systems thinking is complementary, and therefore revealing. As Meadows puts it: “You can see some things through the lens of the human eye, other things through the lens of a microscope, other through the lens of a telescope, and still others through the lens of systems theory. Everything seen through each kind of lens is actually there. Each way of seeing allows our knowledge of the wondrous world in which we live to become a little more complete. At a time when the world is more messy, more crowded, more interconnected, more interdependent, and more rapidly changing than ever before, the more ways of seeing, the better” (Meadows 2008)p. 6).