By Pete Barbrook-Johnson and Alexandra S. Penn
2. Alexandra S. Penn (biography)
What are some effective approaches for developing causal maps of systems in participatory ways? How do different approaches relate to each other and what are the ways in which systems maps can be useful?
Here we focus on seven system mapping methods, described briefly in alphabetical order.
1. Bayesian Belief Networks: a network of variables representing their conditional dependencies (ie., the likelihood of the variable taking different states depending on the states of the variables that influence them). The networks follow a strict acyclic structure (ie., no feedbacks), and nodes tend to be restricted to maximum two incoming arrows. These maps are analysed using the conditional probabilities to compute the potential impact of changes to certain variables, or the influence of certain variables given an observed outcome.
2. Causal Loop Diagrams: networks of variables and causal influences, which normally focus on feedback loops of different lengths and are built around a ‘core system engine’. Maps vary in their complexity and size and are not typically exposed to any formal analysis, but are often the first stage in a system dynamics model.
3. Fuzzy Cognitive Mapping: networks of factors and their causal connections. They are especially suited to participatory contexts, and often multiple versions are created to capture diverse mental models of a system. Described as ‘semi-quantitative’, factors and connections are usually given values, and the impacts of changes in a factor value on the rest of the map are computed in different ways.
4. Participatory Systems Mapping: a network of factors and their causal connections, annotated with salient information from stakeholders (eg., what is important, what might change). Maps tend to be large and complex. They are analysed using network analysis and information from stakeholders to extract noteworthy submaps and narratives.
5. Rich Pictures: a free-form drawing approach in which participants are asked to draw the situation or system under consideration as they wish, with no or only a handful of gentle prompts. This method is part of the wider group of soft systems methodologies.
6. System Dynamics: a network of stocks (numeric values for key variables) and flows (changes in a stock usually represented by a differential equation), and the factors that influence these. Normally, these maps are fully specified quantitatively and used to simulate future dynamics.
7. Theory of Change Maps: networks of concepts usually following a flow from inputs, activities, outputs, and outcomes to final impacts. Maps vary in their complexity and how narrowly they focus on one intervention and its logic, but they are always built around some intervention or action. Maps are often annotated and focused on unearthing assumptions in the impact of interventions.
How do these methods relate to each other?
The following three figures show how these methods relate to each other. While individual projects could use any of these methods in a different way, these figures give a rough sense of where these methods sit in relation to one another, and what some of the most important axes on which to differentiate them are.
The first figure looks at the overall focus and nature of the different system mapping methods.
The second figure focuses on the mode and ease of use of the different system mapping methods.
The third figure presents the outputs and analysis the different system mapping methods produce.
How can systems mapping be useful?
We next suggest five broad types of use, which also apply to most types of modelling or analysis.
1. Helping us think: system maps of all types force us to be more specific about our assumptions, beliefs, and understanding of a system. Many types of systems mapping also force us to structure our ideas using some set of rules or symbols (ie., creating boxes and lines to represent concepts and their relationships). This will introduce simplifications and abstractions, but it will also make explicit our mental models.
2. Helping us orient ourselves: a systems mapping process will often also help us orient ourselves to a system or issue. Whether a map helps us see our, and others’, positions in the system, or whether it helps us quickly develop a fuller understanding of an issue, we will be better oriented to it. This helps people navigate the system better, be aware of what else to think about when considering one part of a map, or know who is affected and so should be included in discussions.
3. Helping us synthesise and connect information: the more flexible types of mapping are particularly good at bringing together different types of data, evidence, and information. They can all be used to inform the development of a map, making connections that would not otherwise be possible. Different types of visualisation, hyperlinking, and map structure can also be used to help people return to the information underlying a map.
4. Helping us communicate: whether we build maps in groups, or alone, and then share them, all system maps should help us communicate our mental models and representations of systems. The process of mapping with others, and the discussions it generates, unearths a multitude of assumptions which can then also be challenged and unpicked. The end product of a mapping process can also help us communicate our ideas about a system. Maps can become repositories for our knowledge which can be accessed by others, and updated, becoming a living document.
5. Helping us extrapolate from assumptions to implications: systems mapping approaches which can be turned into simulations, or which can be analysed in a formal way, also allow us to follow through from the assumptions we have embedded in them, to their implications.
Concluding questions
Are there other methods that you use to develop causal maps of systems and that can be used in participatory ways? What’s the main value that you have found in systems mapping? Do you have other lessons to share from your experience of systems mapping?
To find out more:
Barbrook-Johnson, P. and Penn, A. S. (2022). Systems Mapping: How to build and use causal models of systems. Palgrave-Macmillan: Cham, Switzerland. (Online – open access): https://link.springer.com/book/10.1007/978-3-031-01919-7
Biography: Pete Barbrook-Johnson PhD is a social scientist and complexity scientist working on a range of environmental and energy policy topics, using systems mapping, agent-based modelling, and other related approaches. He is a Departmental Research Lecturer at the University of Oxford in the UK and a member of the Centre for the Evaluation of Complexity Across the Nexus (CECAN) hosted by the University of Surrey in Guildford, UK.
Biography: Alexandra S. Penn DPhil is a complexity scientist working on combining participatory methodologies and mathematical models to create tools for stakeholders to understand and ‘steer’ their complex human ecosystems. She is a Senior Research Fellow at the University of Surrey and a member of the Centre for the Evaluation of Complexity Across the Nexus (CECAN) hosted by the University of Surrey in Guildford, UK.
Interesting, but none of the methods illustrated are in fact systems maps. Systems mapping has nothing to do with CLDs (causal loop diagrams) /System dynamics. Systems maps illustrate imprecise porous boundaries, systems and sub systems. A sub system can belong to more than one system. Systems maps can be drawn either from an individual or group perspective and illustrate their perceived boundary. They can also be used to illustrate different perspectives developed by different people/groups. Systems maps can be developed further into “influence diagrams.”
See also cognitive and causal maps (SODA (Strategic Options Development and Analysis) – Eden/Ackerman)
See also the work of Mitroff and Lindstone and why certain people will always adopt one very specific world view irrespective of the context. And the work of Rosenhead J, on PSMs – problem structuring methods. Useful diagramming/sensemaking methods include:
systems maps to illustrate perceived boundaries, systems and sub systems and different perspectives
influence diagrams
Relationship diagrams
Activity sequence diagrams
Cognitive and casual maps (These are not CLDs)
Ashby’s regulator model – 1st order cybernetics – the role of the regulator/control mechanism
Thanks – agree with much of what you say, but of course I disagree that ”none of the methods illustrated are in fact systems maps”. We discuss our view of systems mapping in the introduction, the list of methods we focus on is indeed narrow and we do not claim to cover all types of system maps. We are only looking at one subset of methods, but we do go broader than CLD (causal loop diagrams) and SD (system dynamics). I do not think definitive lists of what is or what is not systems mapping are helpful. It is a vague term which can refer to many things. We try to live by this, but of course since we picked a particular subset to explore in detail in the book, sometimes this point gets lost.
Peter, thankyou for your reply. Much of the confusion arises because of the word “system” and also the popular American view arising from System Dynamics, Meadows and Senge. Irrespective whether not one is talking about “systems in mind” or “systems in world” they are still mental constructs. It is the observer who decides the boundaries, perspective and interrelationships.
I enjoy Churchman’s take on this: “Indeed, the selection of a definition of “system” is a design choice, because throughout this essay it is the designer who is the chief figure. In other words, whether or not something is a system is regarded as a specific choice of the designer” Churchman, C. West; The Design of Inquiring Systems.
And also Stafford Beer: “There is no doubt that what counts as a system is determined by the observer who demarcates its boundaries for his/her own purposes”.
Checkland hit the nail on the head when he said: “Thus the use of the word “system” is no longer applied to the world, it is instead applied to the process of dealing with the world. Experience shows that this distinction is a slippery concept which many people find very hard to grasp. Probably because embedded in our habits is the way we use the word system” .
Sir Geoffrey Vickers, an eminent British Systems Thinker, talks about resisting our urge to view organizations/social systems in terms of “systems”. One underlying theme in Systems Thinking is that the whole is more important than the parts. This brings into question – who is defining the whole? Systems are theoretical constructs rather than real entities in the world. This is the idea that the systematicity is not in the real world, but in how we view the world. Vickers realized that the very word “system” had become dehumanized.
Systems mapping which has been in existence well before it became popularised as CLDs (causal loop diagrams) is totally misunderstood by the SI community. Systems maps are used to illustrate perceived boundaries and perspectives. This view has been taught at undergrad and post grad for the past 50 years or so.
In my view to mix up several different diagramming methods under general label called “systems maps” has led to much confusion. Systems thinking systems practice is underpinned by some 20 or so key concepts and ideas of which an understanding perspectives, boundaries and interrelationships is critical. Without this poplar ideas/fads such “systems change” and “whole system change” is a nonsense.
Thoughts,
Regards, Geoff Elliott
07979 241348
Thanks – as before, I agree and like all of what you describe. But I don’t follow you on why using the term ‘systems mapping’ to refer to a range of diagramming and modelling methods which all in some way consider boundaries, perspectives, dynamics, influences etc etc in systems, causes confusion or is worth pushing against. Could you elaborate on why this is problematic exactly? The purpose, pros and cons, and roots of each method is not lost, and the broader ideas and history are not forgotten. Instead, I think researchers, analysts, and practitioners find it useful to understand broadly related sets of methods and which might be right for them in particular circumstances. If we draw too many divisions between methods and subfields, we fall into silos and can’t see what else is around that is similar. This was part of our motivation for the book.
Peter, to answer your question: Could you elaborate on why this is problematic exactly……
System Dynamics causal loop diagrams (stock and flows) and causal diagrams are fundamentally about relationships albeit causal / cognitive mapping (Eden/Ackerman) also takes into consideration bi polar constructs, consequences and sets.
System mapping considers perspectives and boundaries hence the distinction given that a systems is simply a mental construct. Often systems maps developed by an individual/group will contain systems and sub systems which currently DO NOT exist. This is done to allow possible future relationships to be identified either within the boundary perceived by the authors and/or possible relationships across the boundary (inter and intra relationships). CSH – Critical Systems Heuristics utilises boundary critique hence systems mapping from the perspectives of: Those affected by and those impacted by” is extremely powerful. This approach is used to help justified or not, eg, international development projects as opposed to the use of “log frames”
I agree, there is not a single diagramming method which fulfills all needs. To group all these under the general term of “systems maps” I see as being problematic as clarity is needed between taking a:
system view
causal / influence view
relationship view
etc
so that critical questioning and directed learning can occur. To draw a causal diagram and call it a systems map does not not address visibly boundary setting and perspective.
SODA cognitive/causal mapping allows via the use of sets for different perspectives to be shown, eg, a:
people view
technical view
IT view
operational
Strategic
etc
Regards
Geoff Elliott
Thanks Geoff, I think understand now, though I do not agree it is problematic. I think we can still preserve clarity about the purpose, strengths, and process behind any individual map or method, while using the term ‘systems mapping’ to capture a wide set of tools. If we are too prescriptive about broad terms, and especially ones that are used in a huge variety of ways, we risk closing off useful connections and related methods/ideas.
I like the way this piece uses the term, and even has a diagram hinting at the differentiation you describe – https://medium.com/disruptive-design/tools-for-systems-thinkers-systems-mapping-2db5cf30ab3a
Peter, to follow up. Thankyou for the reference. I have to disagree, it is problematic. It is important to make and have a clear distinction between the different types of diagramming methods / techniques as these are an essential means of communications and understanding. In particular a clear distinction between methods which focus on boundaries, perspectives or interrelationships. These are used for different purposes. I also disagree with your point about closing off useful connections and related methods/ideas.
An essential Systems Thinking Systems Practice competence is being able combine and synthesize different diagramming methods for different situations/audiences/cultures whilst retaining clarity noting that many people have never been exposed to the range of different methods hence my unease about using the phrase “systems mapping” as generic catch all.
Can I reference:
https://www.open.edu/openlearn/science-maths-technology/engineering-technology/systems-maps
A little bit of history. We were utilising these methods at IERC (International Ecotechnology Research Centre)/Cranfield some 30 years ago on the executive workshops. IERC was set up by a major Japanese Auto Company to sit over the Business School, Shrivenham, Silso etc to explore the use of systems thinking systems practice ideas /concepts to deal with messy unbounded problematic situations as opposed to the use of hard systems techniques. IERC published a hand book: A guided tour of diagramming methods, a for-runner of the above OU (Open University) reference..
Likewise, the “PoD” at LSE (London School of Economics) made use of the distinctions between boundaries, perspectives etc as part of their executive programmes on decision making and multi attribute trade offs. The “PoD” at LSE (London) is a 360 degree interactive decision support centre.
Thoughts, regards
Geoff Elliott
Thanks – we will have to agree to disagree then. But I completely agree we need to understand the differences between methods – again, a key motivation for our book.
I have not come across the IERC handbook and can’t find it online now. It sounds great – any idea where I could get hold of a copy (online or hardcopy)?
Ditto on the PoD at LSE – a quick search returns nothing – do you have a link or reference?
Yes, I have an original hard copy plus copies of other materials produced for exec programmes
Hi Peter, I know we agree to disagree. However, can I make some additional points.
Several reasons why “systems mapping” as described in the OU (Open University) reference below and as used at IERC (International Ecotechnology Research Centre) and global organisations on international development projects is the identification of the “system of interest” and or “systems in focus” from the perspective of an observer.
Systems approaches such SSM (Soft Systems Methodology) and VSM (Viable System Model) make use of these concepts. The “system of interest” and or “system in focus” can be further explored utilising PQR** analysis and depending on the level of abstraction, activity flow diagramming and IDEF (Integration Definition) (0) – 1st order cybernetics. This is extremely important as the control mechanisms for both open and closed systems determine the input/output/outcome conditions. Often the control mechanisms are framed by Policy Setting and Policy Cascade, eg, from S5 to S1 (operational level)*
This is something not easily achieved via the use of casual maps.
https://www.open.edu/openlearn/science-maths-technology/engineering-technology/systems-maps
Thoughts
Regards
Geoff Elliott
* Moderator: this refers to the Viable System Model systems – see Angela Espinosa’s i2Insights contribution: https://i2insights.org/2023/01/24/viable-system-model/
**Moderator: The PQR-formula – A formula useful for defining the root definition in soft systems methodology. It is applied by answering the questions: what should be done (P), how it should be done (Q) and why it should be done (R)
To add to my last point. There seems to be some confusion over the role of “rich pictures”. Rich Pictures along with PQR* analysis are part of SSM – Soft Systems Methodology. The generation of Rich Pictures from an individual or group perspective has NOTHING to do with systems mapping. Soft systems methodology (SSM) is an approach for tackling problematical, messy situations of all kinds. It is an action-oriented process of inquiry into problematic situations in which users learn their way from finding out about the situation, to taking action to improve it. Rich pictures are about illustrating a problematic situation and as such may allude to several systems and sub systems the boundaries of which are not explicitly illustrated
*Moderator: The PQR-formula – A formula useful for defining the root definition in soft systems methodology. It is applied by answering the questions: what should be done (P), how it should be done (Q) and why it should be done (R)
Thanks Geoff. I think it is abundantly clear we have different views about the appropriate terms. For what it is worth, my sense is that your terminology flows from previous work (which you cite) and mine flows from common usage from a broad set of practitioners and researchers today. Your emphasis is on precision and differentiation between methods from the start, my emphasis is on inclusion and differentiation at a later stage (i.e. once people are interested in doing something). I think we agree on what the various methods are and what they are useful for.
Personally, I think these are just presentational choices, semantics if you will, and should not make significant difference on their own to the quality or content of work done with any of the methods we have discussed.
We explain in the book why we included Rich Pictures, and explain the wider SSM context briefly. We had a great chat with Stephen Morse, you might like his book if you have not seen it already – https://www.routledge.com/Rich-Pictures-Encouraging-Resilient-Communities/Bell-Berg-Morse/p/book/9781138898738
Systems mapping can be instrumental in highly complex problem solving.
Systems mapping can facilitate the collective and shared understanding of complex problems: While there is a wide range of systems mapping tools available, many people lack a deep understanding of social-ecological systems. Intervening in the social-ecological systems without understanding them can hamper impact and even result in unintended negative consequences.
And indeed, this community blog has made their vital contribution better known.
These two links may also be of interest to readers:
– https://www.linkedin.com/posts/complexity-academy_interesting-stuff-quantity-the-number-activity-7060557314910482432-qkT3?utm_source=share&utm_medium=member_desktop
– https://www.weforum.org/agenda/2023/03/systems-mapping-can-facilitate-the-collective-and-shared-understanding-of-complex-problems/
1. One other thing worth mentioning is that Pete and Alexandra’s excellent book is available in (free) downloadable pdf form here; https://link.springer.com/book/10.1007/978-3-031-01919-7#toc Well done for making the book so accessible!
2. Their book has a chapter titled “What Data and Evidence Can You Build System Maps From?” and a section therein titled “Using Qualitative Data to Build Your Map” Up until now this has involved quite a lot of time consuming manual coding of text material, albeit helped by the different software packages mentioned in this section. But with the advent of ChatGP and the like, extraction of causal relationships from text is now much simpler and quicker, though not without its pitfalls. Steve Powell, mentioned in this same section,has written about this new capacity here https://www.causalmap.app/post/chatgpt-is-changing-how-we-do-evaluation-the-view-from-causal-map and I have written more generally about ChatGPT’s capacity for qual analysis here: https://mande.co.uk/2023/lists/software-lists/using-chatgpt-as-a-tool-for-the-analysis-of-text-data/
fyi, rick davies
Thanks Rick – I would be very interested in exploring more what Steve has been thinking about. I agree the potential to quickly build robust causal system maps with tools like ChatGPT is very exciting. I see this as another way of doing ‘data-driven’ systems mapping, like we do here, but with time series quant data – https://www.inet.ox.ac.uk/publications/no-2022-26-using-data-driven-systems-mapping-to-contextualise-complexity-economics-insights/
A really helpful introduction, which is expanded on clearly and engagingly in the full book. We’ve learned so much from Alex and Pete’s work in the development of new guidance for systems mapping in population health research, policy and practice – coming very soon!
Thanks Ben! I think your more bespoke / discipline focussed guidance is invaluable – need this in other areas too.
I was just talking about some of the chapters in this book with a colleague and mentioned it as a great primer and introduction. Clearly written and informative for those surveying the field! Congrats Alexandra and Pete and thanks for your contribution.
Thanks Steven – means a lot from someone who has done so much great work in this area!
Interesting summation of a competency I think should be in every leaders toolkit no matter what their field for the reasons you state. Two other systems mapping approaches I use are called Conversation Mapping (a version of rich picturing for those to shy or unable to draw) that organises the perceptions multiple stakeholder have of a systems (as in SSM – soft systems methodology) and Coherence Mapping which explores the relationships between nodes in a system using the question, ‘what do you need from me to achieve your contribution to the whole’s fulfilling its purpose?’ The Coherence map works well in an ‘is-ought’ exploration or when planning a new intervention. Both approaches reveal many of the hidden assumptions that stakeholders hold about the systems they are involved in. The answers you get to your concluding questions would make a great follow up post.
Thanks – would love to know more about these two – do you have any favourite resources / writing on them?
They are both part of the courses we teach and I’d be happy to send you the appropriate course notes if you provide me with a contact address. My email is bruce@besystemics.com There is a YouTube video of me introducing Conversation Mapping about 12 years ago to a group in California at https://youtu.be/uqwL4k2easU
Thanks – will email
A timely post for me! Thanks for sharing! Have you used giga-maps much in your approach and if so, how does the method work for you alongside the other maps you mention? I haven’t used the method myself so don’t know too much about it. But I’m interested in how to qualitatively map the complexity of a system. Rich pictures I find is a really great and simple way to do this. It resonated with me. Thanks.
Hi, I have not used gigamaps before, and we dont focus on them in the book, but we do point to this resource, which is a good place to start I think – https://systemsorienteddesign.net/what-is-gigamapping/.
Nice approach! The iMODELER as a tool combines system dynamics, CLDs (causal loop diagrams), FCM (fuzzy cognitive maps) and to an extent the sensitivity model by Prof. Vester: https://www.consideo.com/files/consideo/pdfs/papers/eng/Why_iMODELER.pdf
Nice, I had not come across this before, will check it out. What do you think the USP (unique selling point) of this software is, compared to others?
The paper should list the software’s unique selling points. It all started from an EU research project to make system dynamics easier. We than continued to explore qualitative modeling approaches and developed our own which started with a rough weighting of connections using the attributes “weak”, “medium”, and “strong” and then continued to go beyond the Fuzzy Cognitive Maps …. It offers a bionic view switching perspectives to handle very large models and to work collaboratively with teams on the same model. The iMODELER also features process and resource factors and some algorithm to identify constraints according to the Theory of Constraints and to come up with optimal sets of parameters for a given goal. And it offers the use of an expert system (know-why.net) to get some proposals for potential factors which as a matter of fact we are currently reviewing in the light of ChatGPT and similar tools. So I am really excited to read the comment from Rick Davies. But that is just the tool – you emphasize the experiences from using the different approaches. We use 4 questions to facilitate the collection of crucial factors translating the natural language from a workshop into cause and effect relations. After a third of the time collecting the arguments we use another third to weight the connections and then the final third to look at the system, its loops and the insight matrices that tell what factors (targets, measures, obstacles, etc.) seem to be the most effective short, medium, and long term. If there is time for more and one wants to know how and with what likelihood things are probably going to develop the de facto causal loop diagram can be translated into a quantitative system dynamics program without the need to switch to a stock and flow diagram. However, the development of a system dynamics model collecting data and developing formula is usually not a participative effort.
Thanks – I will take a close look, for one!