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Can You Fix the American Health Care System? ReThink Health Dynamics

Can You Fix the American Health Care System? ReThink Health Dynamics

Experience first hand the ReThink Health Dynamics Model used by Dartmouth, Brown, MIT, Atlanta, San Diego, Cincinnati, and many other universities and communities throughout the United States. Thousands have come together to explore how they might steward regional resources to achieve the Triple Aim (improve health, cut costs, and quality of care) and beyond (equity and worker productivity).

In this webinar, we:

• Learned how this System Dynamics simulation model has been used to create change,

• Converged on a sound strategy for achieving the Triple Aim, and

• Got a chance to test drive the simulation in an experience much as the one had by real communities doing real work.

And the best part is that this simulation is free for classroom and community use, so you can provoke a more fruitful conversation about how we can make real progress in population health.

Learn more about the Seminar Series.

Watch the recording below

Whoops, this recording is available for members only. If you have a membership, please log in. If not, you can definitely get access! Purchase a membership here. If you're not a member but have purchased a ticket to this webinar, please contact us at office@systemdynamics.
org

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Housing Dynamics

Housing Dynamics

We had an insightful conversation with David Stroh, Martijn Eskinasi, and Kaveh Dianati at our latest seminar. We learned about how using causal loop diagrams based on simple archetypes, illuminate interdependencies across housing availability, wealth inequality, homelessness, and economic development. We explored the dynamics of the housing crisis in London and how System Dynamics is helping the Dutch Ministry of Interior make better housing polices

Learn more about the Seminar Series.

Responses to Housing Dynamics Panel Questions

DAVID STROH:

David’s cautionary tale suggests avoiding early complexity in engagement with the problem owner. Does he have a method for keeping it simple?

I use a four-stage process to engage stakeholders in applying systems thinking to catalyze real change. Systems analysis, the second stage, is just one part of this overall change strategy. The analysis itself primarily draws on systems archetypes to simplify complexity. At the same time, building on individual archetypes and identifying multiple ones provide complexity while retaining the power of illuminating recognizable storylines. For more information, see my book Systems Thinking for Social Change (Chelsea Green, 2015).

How do you collect data for these projects and how you do model assumptions about specific issues you can’t collect data for?

Primary data comes from interviews with a diverse set of stakeholders – both decision makers and people closer to the front lines. Secondary data comes from written documentation provided by the stakeholders. We (often Mike Goodman and I) enlist a modeling team drawn from these stakeholders to test and refine the initial models we build – often by having people first build their own simple models based on what we see to be the relevant archetype(s). We also collect and add mental models to the qualitative causal loop diagrams to help them see how their mental models impact the system dynamics.

Can you name examples of elites fanning ethnic conflicts? Is there really an elite behind this or is this potentially too, a structural issue?

One need look no further than the Republican Party in the U.S., and the elite donors who fund them, for an example of fanning ethnic tensions – between whites and not only blacks but also immigrants. I first came across this dynamic nearly 20 years ago in advising a group of NGOs in Burundi who was looking to rebuild civil society thereafter the war between Hutus and Tutsis had almost destroyed their country. To me, the existence of an elite IS a structural issue. See for example my recent article “Overcoming the Systemic Challenges of Wealth Inequality in the U.S.” in The Foundation Review.

How do you deal with the delay of the long-term solution where the workers are needed within a short time to keep the economic development happening?

In any Shifting the Burden dynamic, the key is to reinforce investment in the long-term solution while either discouraging the quick fix or seeking to mitigate (or even reverse) the negative impacts of the quick fix on the fundamental solution.

David – curious why you leave out the link polarities. As a System Dynamicist, this makes it harder to validate your assumptions.

I leave out polarities in my presentations to stakeholders because they are covered by how I translate loops and archetypes into everyday recognizable language and stories. I occasionally use different colored links for + and – since they are a little easier to make sense of.

In Los Angeles, we have a serious homelessness challenge which is quite visible. Can you comment on how your work can address the challenges here?

The change process is as important as the insights it generates. I don’t know enough about the politics of LA, what has been tried so far, who has been involved and who has been excluded, etc. to comment.

to all speakers: advocators of big data research state that with the amount of data available nowadays it is more promising to look at correlations than causation

There is never enough data nor will there ever be. The problem in influencing how people think is often not insufficient data, but insufficient attention to the non-cognitive aspects of systems change – such as the emotional, behavioral, and spiritual issues involved. See for example the last chapter of Systems Thinking for Social Change and the blog post “Systems Thinking: It’s Not (Just) What You Think”.

KAVEH DIANATI

How do you collect data for these projects and how you do model assumptions about specific issues you can’t collect data for?

In the case of the work on London’s housing crisis, most of the data were collated from publicly available government statistical sources. Often, data is incomplete and/or contradictory between different sources and you have to address these issues on a case by case basis. In the case where data for a particular key parameter is not available, a reasonable expert estimate can be used to let the model run, and sensitivity analysis must be carried out to understand the impact of the uncertainty and results and policy recommendations.

Kaveh: to what degree do you expect that your model/findings would also apply to other cities (with different parameterization)?

To a large extent, the dynamics described in this work apply generally to attractive metropolitan areas in liberal advanced economies, where housing is regarded as an attractive investment asset and where housing is financialised, and where unregulated mortgage lending by commercial banks is driving house price inflation.

What would be the policy leverage points to keep the system “in balance” at a reasonable affordability level for housing, avoiding the exponential growth and boom and bust cycles?

As explained during the presentation, key recommended policy levers are macroprudential policies such as imposing restrictions on loan-to-value and loan-to-income ratios, as well as requiring banks to base their property valuations on a moving average of past prices when issuing loans. In parallel, affordable housebuilding programs must take off again to ensure access to housing to the lowest decile households.

What role do zoning rules play in the reduction of housing construction in London?

There is a great recent paper published on that by Gallent et al (2021) titled “Is Zoning the Solution to the UK Housing Crisis?”. Zoning has been suggested by various authors as a policy to accelerate supply, and my modeling shows that easing planning restrictions can have a significant impact on housing supply and therefore slow down the worsening of affordability. So, zoning is very important. However, note that, as I explained during the presentation, this would have no impact on mitigating the boom and bust cycles, because these are not related to the supply side but rather to the demand side. Furthermore, housing supply is necessarily finite while demand that is backed by newly created mortgages and international footloose capital is virtually infinite, and therefore without regulating the demand side, supply-side policies are not enough to address the housing crisis.

Can you comment again on the large dip in the near future projection around 2045 – 2050?

This has to do with the ‘bust’ period of the recurring boom-and-bust cycles, which happens when the burden of housing-related housing debt becomes unsustainable, putting pressure on household consumption, savings, economic investment, productivity growth, and the economy as a whole over the long term, feeding back to restrict new mortgage lending and demand for housing, triggering all the reinforcing mechanisms (Investment Loop and Housing-Finance Loops) in the opposite direction of growth and leading to a precipitous fall in house prices and mortgage lending.

A general question. When starting out on building a model, is it the speaker’s typical first step to hunt for the available data? What was the first thing done when tackling such a wicked problem as housing?

The first step in the System Dynamics method is problem definition via formulating a number of reference modes, i.e., past behavior of key variables over time. So yes, you could say that at the outset, especially in a quantitative modeling study, I would look for historical data on key variables of interest and look at how they have been developing over the past. The next step is then to try and understand these developments from a systemic feedback-centered perspective.

To all speakers: advocators of big data research state that with the amount of data available nowadays it is more promising to look at correlations than causation (‘let the data speak for us’); this would somehow remove the inherent bias of our models; what is your opinion on this criticism?

First, correlation methods are unable to explain the “why”s, i.e., explaining why things behave the way they do. In other words, they are unable to tell interesting ‘stories’ that capture our collective imaginations and can mobilize society’s forces towards our common goals. The feedback-oriented explanations offered by System Dynamics offer such relatable narratives that are powerful communication media. Secondly, since correlation methods base their forecasts solely on past behavior, and do not model the structure of the system, more often than not they involve extrapolation of current trends and are unable to foresee or warn about potential reversals in trends.

How do you validate these housing models? Do you use publicly available data/records?

Yes, for behavioral validation. For structural validation, you need to follow the best practice suite of tests available (e.g., sensitivity tests, extreme condition tests, etc.) as explained clearly by Barlas (1996) “Formal aspects of model validity and validation in system dynamics”.

The London CLD seems to focus on financing the DEMAND side. What about the SUPPLY side? More construction would reduce prices. What is inhibiting construction?

There is extensive discussion about that, in particular around issues such as increasing concentration and consolidation in the housebuilding industry, as well as issues around land banking. These aspects were fully addressed in my thesis but excluded from my model, due to reasons discussed extensively in the thesis, to be available hopefully soon online.

Kaveh, you indicated things can’t grow forever so when in the future does the model crash?

Rather than focusing on “when”, I would like to emphasize that the tendency for boom-and-bust cycles is embedded into the structure of the system, but no one can tell you when exactly. However, if ‘your doctor tells you that you will have a heart attack if you do not stop smoking, this advice is helpful, even if it does not tell you exactly when a heart attack will occur or how bad it will be’ (Meadows, Richardson, & Bruckmann, 1982, p. 279).

MARTIJN ESKINASI

David’s cautionary tale suggests avoiding early complexity in engagement with the problem owner. Does he have a method for keeping it simple?

In general, it is good practice to stick to small comprehensible models. I’ve got bad experiences with large models, which can become unmanageable quickly. If possible, implicit System Dynamics models in your field of interest can be translated to stocks and flows. This also helps comprehensibility in contact with stakeholders

How do you collect data for these projects and how you do model assumptions about specific issues you can’t collect data for?

In the Netherlands, there is also lots of statistical data available. Expert guesses are another useful source. But is it not only about data, it is also about system structures.

What would be the policy leverage points to keep the system “in balance” at a reasonable affordability level for housing, avoiding the exponential growth and boom and bust cycles?

I’d agree with Kaveh here too. Lots of other works point in that direction. In NL, plenty of feasible scenarios were elaborated for reducing procyclical housing finance. System dynamics will add up here, but there are no breakthrough insights to be found there anymore. But it might be interesting to model political processes why is it hard to reduce or even abolish abundant finance schemes

I would be interested to know more about the link between housing affordability and car-oriented transport policies leading to car dependence and urban sprawl.

Some work was done on that. See Chapter 3 in my Ph.D. thesis. 

How would you ensure that your own bias as a researcher does not lead to unintended consequences? Would you conduct this research in parallel to another researcher, for instance?

That is exactly why I am a proponent of close cooperation with other researchers. Repenniing made a strong case already in 2003.

A general question. When starting out on building a model, is it the speaker’s typical first step to hunt for the available data? What was the first thing done when tackling such a wicked problem as housing?

Not necessarily. I was mostly looking for template models and institutional structures. Data comes later, though in NL we are relatively spoilt with data.

Are you always using your “goal” as one of the elements in your system? ie: The ability to pay for quality housing

Not always. What about finding structures capable of generating reference modes of behavior?

To all speakers: advocators of big data research state that with the amount of data available nowadays it is more promising to look at correlations than causation (‘let the data speak for us’); this would somehow remove the inherent bias of our models; what is your opinion on this criticism?

In public policy, there is nearly always a need to improve system performance. There will be a gap between observed and preferred outcomes and a theory of how measures propagate through the system and reduce the gap. Data won’t tell you that. And data can be interpreted in order to fit any frame, especially if there is a lot of.

How do you validate these housing models? Do you use publicly available data/records?

I agree with Kaveh here

 

Watch the recording below

Whoops, this recording is available for members only. If you have a membership, please log in. If not, you can definitely get access! Purchase a membership here. If you're not a member but have purchased a ticket to this webinar, please contact us at office@systemdynamics.org

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Introduction to Modeling Process

Introduction to Modeling Process

We had 560 people joining us from all over the world at the “Introduction to Modeling Process” with Nici Zimmermann. 

Watch the recording below to:
• Build your very first quantitative System Dynamics model
• Use Vensim software for very basic quantitative modeling
• Familiarise yourself with the System Dynamics modeling process
• Learn how System Dynamics can be used for policy development

Download Vensim PLE – The free System Dynamics modeling software from our sponsor Ventana Systems

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System Dynamics for Climate Change Mitigation

System Dynamics for Climate Change Mitigation

We had an insightful Webinar with the participation of With Juliette Rooney-Varga, Carolyn McCarthy, Sibel Eker, and Steve Arquitt .

Integrated System Dynamics models of economy and environment have long been used for research and decision support for sustainability problems, starting with the seminal work of World Dynamics and Limits to Growth. We discussed how System Dynamics models support decision-making, stakeholder, and public engagement for climate change and sustainability problems. We reflected on existing models and tools, such as Climate Interactive’s En-ROADS and Millennium Institute’s iSDG tool, and their use cases. We also discussed how the Climate Change Initiative at UMass Lowell uses System Dynamics tools to raise awareness on climate change.

If you’re a member, you can watch the webinar recording here.

Below are the answers to questions asked live during the Webinar.

Learn more about the Seminar Series.

Q&A Seminar | System Dynamics for Climate Change

Climate Interactive:

How would you describe the interaction between complex models (GCMs …) and simpler system dynamic models in more detail? (how can they support each other?)

Shortly, large detailed models help for cross-validating the simpler models. In return, simple models support the complex models in stakeholder engagement and scenario co-production.

What are the similarities between the EN-Roads Model & the iSDG Model? What are the main differences?

Both EN-Roads and iSDG are based on the System Dynamics method. Both emphasize transparancy, user friendliness, and shared learning. Both place great emphasis on facilitation and support in shared learning. The differences: EN-Roads is a global model, where iSDG is customized to support planning in a particular country or geographic region. EN-Roads is focused on strategies to keep global temperature below a specified level, where iSDG’s focus is more diffuse taking on all the SDGs.

What are some of the major impacts that the Climate Interactive team see on the application side of the models?

This question was not clear to me during the webinar. If “application” means the use of Climate Interactive’s models, we see quite a substantial impact. Only En-ROADS has been used in 73 different countries so far, engaging almost 63000 people. We have a wide audience, from policymakers and philantropists to higher education students and community members. One of the most striking and uplifting recent examples of En-ROADS outreach is the events organized by one of our ambassadors with smallholder farmers in Tanzania. 

Why don’t you use python as the intermediate language? Thanks

Answered during the webinar. Python is a user-friendly language but not as fast as C. We need speed in interactive simulators, so the Vensim model is converted to C.

Are system dynamics models being used in conjunction with Big data and AI?Can system dynamics models learn with machine learning?

There are initiatives about this as far as I know, and ML is very useful for quantifying empirical relationships, but outsourcing the model building completely to AI is not possible, neither desirable in my opinion. System Dynamics’s main strength lies in its descriptive nature, accessibility and understandability. While a hard coupling of SD and machine learning can provide many benefits, it might override the main strengths.

Since there seems to be many questions/comments regarding implementation/compliance, might it be helpful to start focusing on modeling the topic of governance itself, in order to identify and understand the influencing dynamics and loops on the gaps between the ideal solutions actually implemented?

In general, especially regarding specific sustainability governance problems, I agree that this should be the approach, because problem delineation and understanding the system strructure is key to developing any solution. In En-ROADS, though, the primary purpose is public engagement around the topic of “solutions”, hence the underlying dynamics are not co-modelled but shared with the users through various indicators and graphs.

Does the Climate Interactive climate-economy feedback have anything to do with Nordhaus’ “damage” function?

Since En-ROADS is an interactive simulator, it includes a damage function that allows the users to experiment with various “damage functions” found in the literature, including Nordhaus, or make their own assumptions. You can read more about it here 

When will the nature-based/land-based parts in En-ROADS be accessible online?

In the next few months. Please check either the En-ROADS simulator or this page

Very interesting presentation Sibel. Can SDeverywhere and the implementation into a website be done by somebody completely unfamiliar with C or Java or any programming? Many thanks.

I must say that it would be a bit challenging for someone who has no programming experience. There are guidelines, though, which might be helpful to get started.

Questions to Millennium Institute

What are the similarities between the EN-Roads Model & the iSDG Model? What are the main differences?

Both EN-Roads and iSDG are based on the System Dynamics method. Both emphasize transparancy, user friendliness, and shared learning. Both place great emphasis on facilitation and support in shared learning. The differences: EN-Roads is a global model, where iSDG is customized to support planning in a particular country or geographic region. EN-Roads is focused on strategies to keep global temperature below a specified level, where iSDG’s focus is more diffuse taking on all the SDGs.

Are parts of iSDG Model publically available?

Yes, go to www.millennium-institute.org/isdg . There you can access a demonstration model, videos on the iSDG, and the model documentation.

To what extent is the Millennium Institute SDG model open source? It would be so nice to use it rather than starting modelling from scratch in every research project.

At this time the iSDG is not open source. iSDG models are developed within the frame of a specific project. However, much can be learned about the model and its structure by visiting www.millennium-institute.org/isdg.

@Steve, how do you integrate “indicators” of SDG’s to report a single metric?

The iSDG reports the status of each of the 17 SGDs separately. The level of performance of the targets falling under each SDG are averaged to calculate the SDG performance. Targets can be thought of as desired levels of indicators. For a complete explanation see https://www.pnas.org/content/pnas/suppl/2019/10/29/1817276116.DCSupplemental/pnas.1817276116.sapp.pdf

SDG and how it is implemented in real world is highly context-dependence – how iSDG address this?

The iSDG is customized for the country or regional setting. Workshops are held with local experts, decision-makers, and stakeholders who review the model and identify key issues and policies to include inthe iSDG model.

Steve’s question regarding connecting real action to the plan is important. How do we make the interactive modeling tools an integral part of follow up and feedback on action?

With climate change and the SDGs both this really hits the crux of the matter. With the iSDG it is important to involve a broad spectrum of stakeholders on the modeling team and in the workshops who are motivated to see that the selected scenarios are being transformed into policies and then funded. This will require a well-trained team that can run scenarios, derive policies and work with the relevant government people to assure implementation. Monitoring is essential, and needs to be built into the projects. I fully agree with Juliette that the models need to engage with citizens who will then push leaders to make the necessary changes. I would love to hear others’ ideas and experiences on this.

Why choose poverty as a key #1 SDG?

“No poverty” as SDG1 was defined and designated by agreement of the 193 Agenda 2030 signatory countries. There is debate about which SDG is the most important. The iSDG takes no position on which SDG is the most important However, in the iSDG poverty is linked to almost every SDG.

Is this model (MI iSDG Tool) built in STELLA?

If you mean the iSDG, yes the model I showed was built in STELLA however we also have a version in Vensim.

What are some of the active projects that MI is doing today?

Currently we are working on iSDG projects in Afghanistan, Bhutan, China, Uganda, Namibia, Djibouti, Kenya, Democratic Republic of the Congo.

This question–or 2 questions–are for Steve. First, are worldviews and values included in the iSDG models? If so, how? A second question relates to how the highest-level decision-makers regard the models. I’m new to SDS but spent a number of years working with a roughly analogous set of high-level

After some relection, worldviews and values are pervasive in the iSDG model by virtue of the SDGs themselves. iSDG is intended to help policy-makers design strategies and allocate resources for attaining the SDGs. This includes the “leave no one behind” principle, gender equity in education and economic opportunities, equitable income distribution, preserving biodiversity for future generations, rule of law and many others.

Questions to CCI

@CCI any tips on how to engage kids with these tools?

Find resources: Comprehensive Facilitator Resources  Online World Climate Resources

Steve’s question regarding connecting real action to the plan is important. How do we make the interactive modeling tools an integral part of follow up and feedback on action?

Watch the recording for a full answer

@Juliette, could you say a bit about hope? There is a political divide especially in the US, but I read recently that % of the US population who feels anxious about climate change is ~68%. Could role-play games help deal with this anxiety?

Watch the recording for a full answer

“Research shows that showing people research doesn’t work”. What are your thoughts on this @Juliette?

We agree with John Sterman! But if you want to read more about this research, you can here

Why do you think that higher levels of “hope” begin and end higher with the i-H group?

Watch the recording for a full answer

Was the ethnic cultural diversity in your simulation group meetings more diverse than the photos would suggest? If not it’s concerning that you have a rather restricted sample?

Thank you for this question. The breakdown of participants’ racial and ethnic diversity for Building Consensus for Ambitious Climate Action through the World Climate Simulation can be found on page seven. Limitations relevant to our sample can be found on page 24 and reads, “Our sample was not randomly drawn from the general population and is therefore not expected to be representative of the American public. In addition, because the youngest participants in our study were drawn from programs serving low-income, first-generation-to-college students, age likely correlates with other demographic traits in our sample. We therefore do not claim that the observed effects of the simulation or demographics extend to the general American population.”

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Watch the recording below

Whoops, this recording is available for members only. If you have a membership, please log in. If not, you can definitely get access! Purchase a membership here. If you're not a member but have purchased a ticket to this webinar, please contact us at office@systemdynamics.org

Top 10 Tips to Engage People with a System Dynamics Model

Top 10 Tips to Engage People with a System Dynamics Model

Andrew P. Jones is Co-Founder and Co-Director of Climate Interactive and a Research Affiliate at MIT Sloan. Andrew is an expert on climate change and energy issues, a prominent System Dynamics modeler, and a keynote speaker.

In his webinar with System Dynamics Society, Jones presented his 10+1 tips to engage people with a System Dynamics model. Here’s a summary of the tips, but you can watch the recording below for all details!

All Seminar Series are free for members of the Society. Join us today and unlock all benefits!

1. Make it a challenging adventure on their terms in your virtual world
Make your model playful to entice curiosity about what it tests. This is a virtual world where people will experience something new. The challenging adventure or game is what we do mostly with the interface of the model. If you open the En-ROADS interface, you will see two main graphs, the main output, and several sliders. When playing with the sliders, your changes will be reflected in the graphs. Avoid telling people: “I’m going to show you how to do this”, instead, try saying: “On your terms, you’re going to have to figure out how to get that graph down to your target line”

“We do NOT model systems. We model problems.

2. Focus on mental models you want to improve
We do NOT model systems. We model problems. In System Dynamics, we define a problem as a behavior over time, a reference mode that we’re curious about why does it behave like that. We’re so curious about the problem that we develop a simulation to understand it. We build interfaces to improve the mental models of the stakeholders or clients. System Dynamics modelers know that mostly the mental models of decision-makers don’t match with the real world and how the actual system behaves. We don’t build interfaces to give access to policy levers in the system, but we are trying to leverage the necessary mental model improvements.

3. Make participants mentally simulate before running a scenario
If people don’t have a theory, they don’t notice the mental model they use to forecast what’s going to happen. Then they don’t get to learn and improve their understanding. Therefore, you must encourage people to anticipate, based on their own theories, what’s going to happen when running a scenario. No theory, no learning.” (Edward Deming)

“Tell people what to look at, let them guess what they are going to see, and then make it exciting like a movie”

4. Create a dynamic visual experience
Humans like to see change and it is important to employ this fact to get people to run and look at your graphs without losing their focus. Make people think and anticipate and then direct their eyes to what you want them to notice. If you do this well, you don’t even need to draw a Causal Loop Diagram because they are drawing it in their heads. Tell people what to look at, let them guess what they are going to see, and then make it exciting like a movie.

5. Set up participants to talk with each other
People learn socially and with hot-button issues like climate change, they need to know that their friends are not going to hate them if they change their minds. You need people to be processing the information collectively and socially with others. When presenting your model, stop frequently and advise: “Turn to the person next to you and discuss what you think of that conclusion”.

“Keep the discussion on improving system performance not on the tool you’re using”

6. Know along the way that you are playing at least seven roles

Try to present your model with the help of, at least, another person. Ideally, you need someone to facilitate the discussion while another runs the model. As a facilitator, you will be playing four roles including:

Coach – Helping participants to extract insights out of the model.
Professor – Teaching the audience theories and sharing factual information
Playwright – Creating an emotional journey of ups and downs.
Fellow Traveler – Being authentic, vulnerable, and just another person trying to solve a complex problem. If it is worth making a model about, it’s very important. If it is very important, you must deeply care about it.

You want the conversation to be around how to solve a complex problem together and what your audience is going to do about it. Keep the discussion on improving system performance not on “oh that’s a cool model how did you make that”. That’s all side information.

You want to minimize your roles in:
Tech – you must keep the conversation on improving the system performance, not the way or tool you have used to develop the model or create the graphs
Advocate – when people disagree with you, your job is not to fight them or disagree with them back, but to set up others to find the voice of your work.
Defender – Don’t get involved in the fight of “YOU HAVE A BAD MODEL!”. Avoid this fight as much as you can.

Read the article “Teamwork in Group Model Building” on the System Dynamics Review for more insights on strategies for efficient and effective model building in groups.

7. Build confidence and share testing as needed

You can share your tests and comparisons to other models and/or predictions to build stronger confidence. For instance, Climate Interactive and MIT Sloan built the En-ROADS with the best science available, using the data sources such as the Intergovernmental Panel on Climate Change (IPCC) and International Energy Agency. All the assumptions are available open-source in the 400-page reference guide. Many of the assumptions that someone might not believe in are changeable within the model. Several models do not have good literature of other scenarios to compare against, while En-ROADS can be compared with six integrated assessment models to build confidence.

8. Use loops and stock/flow diagrams only to illuminate
As you help people improve their intuition, sometimes you need to use loops and stock/flow diagrams, especially if you are presenting to a more technical audience but always connect it to the simulator. Avoid showing this to policymakers, they are usually not interested in the loops, instead, tell a story about reinforcing or balancing feedback.

9. Make space for feelings and processing

Deliver your presentation with excitement and intensity, but you need to slam on the brakes and let participants compromise with their feelings and do the necessary processing. You may create a scenario of success, and they get to create their vision, something that they would love to see. And it’s time to slam on the brakes and may invite them to 60 seconds of silence. Yes! It is weird but imagine 60 seconds of silence of people sitting with a scenario of success.

“Create the conditions where people are open to changing their minds”

10. Pay attention to three legs of the learning stool
Reflective Conversation – Create the conditions where people are open to changing their minds, surfacing and testing assumptions, and talking to their peers about improving their assumptions. You’ve got to make the space where people are open to being wrong and thinking differently.

Vision – Help people see a future that they fall in love with they just want it so badly that they see the gap between the vision they want and the reality that they feel and experience that tension in between. Orient towards what one genuinely cares about.

Systems Thinking – Explaining how a complex system works where time, cause, and effect are distant in time and space can be difficult, especially when you include stocks, flows, feedback loops, and other inner relationships. You can learn how to facilitate a training that uses systems thinking and System Dynamics for free with Climate Interactive learning resources

10 + 1. Give them the simulator

People need your help as a facilitator, but you must give them something to play with that naturally gives them the mental model improvements that you want and guides them towards committing themselves to action to improve system performance. As Buckminster Fuller states “If you want to teach people a new way of thinking, don’t bother trying to teach them. Instead, give them a tool, the use of which will lead to new ways of thinking.”

Watch the recording below

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System Dynamics Biomedical Modeling

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In this Seminar, authors present their work published on the special issue of the System Dynamics Review on Biomedical Modeling. The special issue brings together new research that explores a fascinating array of biomedical problems, from the modeling of pharmacokinetics, hematologic disorders, and blood cell production to chronic disease progression at an aggregate level. System Dynamics health modelers engage with interdisciplinary teams of medical and policy experts in order to explore exciting new biomedical research opportunities.

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Here some answered questions from the Q&A Session!

Which critical data elements should one collect to gather further insight into model behavior? Were you able to collect medical data to calibrate your model? If not, what are the main drawbacks with respect to your conclusions?

We had to use existing data in the literature for model calibration. But of course, we had some problems with that. First, the data we found was not exact numerical values, rather they were presented in graphs. Second, individual data of patients were not included, giving all the statistics as sample averages. Therefore, we could not delve more into the personalization aspect. Additionally, the literature lacked sufficient blood count data under chemotherapy, making it difficult to calibrate for different chemotherapy regimens. What we actually needed was continuous, or at least a high frequency, time-dependent neutrophil counts for individuals with different characteristics, for example, neutrophil response to a single G-CSF shot for 40 hours and blood cell response in a single chemotherapy cycle. [by Orkun İrsoy & Şanser Güz]

How did you come up with alternative treatments? Was it through experimentation or optimization? 

Since our main focus was not concentrated on finding an ‘optimal’ treatment, we didn’t use any dose & timing optimization procedure. Effectively, our strategy landscape for treatment protocols at https://www.ctontario.ca/review/online-pharmacy/ is defined by two factors: G-CSF Starting Time and G-CSF Injection Count. The standard protocol starts G-CSF supplementation by the end of the fourth day and continues until the next cycle of chemotherapy. Thus, increasing the injections from the end was not an option as it interferes with the next cycle. In our analysis, we reduced the number of injections to create our alternative protocols, to observe the effects of over-and under-stimulation dynamics. We also tested protocols with different starting times (results included in electronic supplement), but the inferences were no different than the one we derived from our current array of protocols. [by Orkun İrsoy & Şanser Güz]

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Responding to The Exponential Demand for Systems Thinking

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Webinar Q&A | The Effect of Institutional Quality on Economic Growth

Webinar Q&A | The Effect of Institutional Quality on Economic Growth

We had an insightful Webinar with the participation of Aman Ullah and Ivan Taylor who presented us with a macroeconomic framework that identifies the structure of institutional quality in developing countries and their linkages to economic growth and income distribution

If you’re a member, you can watch the webinar recording here and download the presentation here

Here are the answers to questions asked live during the Webinar.

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Q&A Seminar | The Effect of Institutional Quality on Economic Growth

Answers by Aman Ullah and Ivan Taylor

1. Can you provide more insight into the feedback loops that were responsible for the differences across the different countries?  What were the primary factors creating the differences?

The institutions that directly impact economic growth are control of income inequality, economic openness, government expenditure, private investment, foreign direct investment. The feedback loops that contain these institutions have the most impact.

 

2. Are there similarities between the feedback loops in the different countries? Do they have pivotal factors in common which are responsible for the behavior of your simulations?

All of the feedbacks in the results are the same for all the countries. The difference from country to country depends on the projected trends in the future quality of the institutions.

 

3. What “insights” came from this model that you didn’t have before you started?

We were surprised by the economic growth projected for Pakistan compared to the decline in economic growth in the other countries. We need to do more research into why this occurred.

 

4. I’m interested in hearing more about how you translated the model from Vensim to Excel.

We used the Euler integration function (default) to solve the differential equations in Vensim. And Euler integration can be translated into equations in the cells of Excel with each stock, flow, and auxiliary as a separate column in the spreadsheet. And in each row, the cells (stocks, flows, and auxiliaries) are updated for each step through time.

 

5. Why specific countries were only modeled – Iran, Greece, S Africa, and Pakistan – what is common in them, and 2)  is there a  country comparison available?

We wanted to select one country from each continent and secondly, we wanted to show that the model applied to countries with different levels of development. Also, we were particularly interested in countries facing different economic growth challenges.

 

6. There seems to be some dynamics in the datasets that are not being captured by the model; are there justifications for observing such behavior? Specifically, it would be great to see natural experiments between countries which show different levels of variations around the simulated values.

1) The calibration of the model tries to draw a smooth line through the highly discontinuous datasets based on minimizing the total squared error. So the lines for some institutions will be a better match to the data than others. It may be worthwhile considering the addition of a few more variables.

2) Yes, we would be very open to the use of natural experiments. For example, many countries have attempted to increase their economic growth using various policies. It would be interesting to examine the results of these policies in natural experiments. This would be very useful to better understand the changes seen in the datasets for individual countries.

 

7. The model doesn’t seem to have any way to incorporate things like the 2008-9 financial crisis,  Covid-19 ( in 2020 #’s), etc. These different years don’t actually seem comparable, as   impact as a function of effort would vary widely based on these other factors

We used the data from 1996 to 2019. So the data from the financial crisis was included. However, some countries were more affected by the financial crisis than others. The model did not consider a shock to the system such as the 2008-9 financial crisis but in general System Dynamics can do that and often considers such shocks.

 

8. What are the units of Policy Effort?

This work is a proof of concept at this time. So we used dimensionless units for policy effort. However, we recognize that policy implementation can be costly and will vary from institution to institution. So in the future, we would like to examine policy effort in terms of cost and effectiveness with the appropriate sensitivity analysis.

 

9. Can you please explain the rationale for introducing inflation as an affecting factor for corruption?

Based on econometric theory and results, there appears to be a strong cause-and-effect relationship between inflation and corruption in the literature. Practically, when there is increasing inflation (such as in Argentina and Turkey), there is a great loss in wealth and people may respond through corrupt behaviors to compensate.

 

10. How did you quantify the effect of the amount of effort on institutional change (e.g. change in corruption)?

When we change the effort, this affects the target level in the goal-gap formula of institutional change. So more effort is expended to achieve a higher target and the model responds by closing the gap between the target and the actual value over time

 

11. Is there any sensitivity analysis?

We did scenario analysis but not sensitivity analysis. Sensitivity analysis can be done quite easily in the model and it should be done in the future. We should have included a sensitivity analysis in the presentation.

 

12. On the System Dynamics model overview why were the loops not labeled?

They should have been labeled. Because we converted all of the values so that higher values were better, all of the loops were reinforcing loops and the differences in behavior occurred because the results of the reinforcing loops could lead to either exponential growth or exponential decline. And that demonstrates the importance of actually building a simulation model

 

13. Is there an underlying assumption in the scenario analyses that increasing economic growth is a good thing?

Because all of the institutions are connected by reinforcing loops, that increasing economic growth will lead to increasing institutional quality and vice versa. We believe that increasing institutional quality is a good thing

 

14. If increased government revenue comes from taxation, might there be a reduction in private investment and therefore economic growth!

Yes, the connection between government revenue and private investment needs to be looked at in more detail. This will be future work.

 

15. Does the model take into account the goals of the institutions for the quality of them?

Yes, because all of the loops are reinforcing then the goals of the institutions are always to improve quality.

 

16. Is there a country comparison available?

Yes, a country comparison is available but wasn’t included as part of the presentation. You can contact us to find out more.

 

17. Is this model being used practically at the moment?

Yes and no, this model is informing a member of the Planning and Development Board of Pakistan. However, the model has not been peer-reviewed. So there needs to be some caution in the interpretation and application of the results at this time. However, similar models have been developed and utilized by the World Bank and International Monetary Fund but not specifically System Dynamics models.

 

18. Does the model/data offer any insight into why Pakistan was the only country that experiencing economic growth?

Yes, the model provides insights into all of the country analysis. In particular, the reinforcing loops in Pakistan result in growth while the reinforcing loops in the other countries are suggesting a decline. More work is necessary to examine these trends in more detail and determine if corrective action can be taken in the countries where decline is projected.

 

19. Can you provide any insight into the relative leverage that one can get from the various policy options?

Yes, the institutions with closer connections to economic growth will have more impact on it. However, some of these will be synergistic and some will limit growth. So in fact, the leverage points are country-specific.

 

20. Can the model be applied in the “developed” world?

Yes, we have applied the model to the United States and Canada and it provided useful insights. We believe that model can be applied to any country in the world if there is data to support the calibration.

 

21. Do you have any insight into how quickly a change in one institution in your model impacts the economic growth rate? That is, what are the delay factors in the model?

Yes, the change in institutional quality requires time and the times are calibrated in the model for all of the institutions separately. So some institutions will change faster and some will be delayed. Again, these times to change are country-specific.

 

22. Would the question of HOW institutions can be improved to drive economic growth be outside the scope of the study?

At present, we haven’t looked at policy implementation. However, our work on policy optimization would require an estimation of the cost and benefits of policy options.

 

23. Did you do one of these for the US?

Yes, please contact us for more information in the case of the US or any other country.

 

24. Did you find that specific institutions tended to be more influential in pushing outcomes? Is this true across all cases?

Yes, income inequality, economic openness, government expenditure, private investment, and foreign direct investment had the most impact. Although this is true for all cases, the amount of impact varies from country to country.

 

25. Can we see the specific parameters that affect the growth in Pakistan?

Yes, please contact us and we will share these results.

 

26. Did you do runs that show your confidence limits for the predicted values  ( based on how good or bad the fit to the time-series of actual data was)?

No, we only tried to minimize the total sum of squared error for all of the institutions. However, it is possible to develop confidence intervals on the parameters and thereby, confidence intervals on the projections. This can be included in future work.

 

27. I didn’t see a graph of  EFFORT put in versus IMPACT, with confidence limits on it.  Where does the $$$ for “effort” come from and how much damage does taking that $$ away from other uses show up in the model?
We assume that a certain amount of effort is being expended on all of the institutions at present. And we are only considering extra effort over and above the effort expended in the status quo situation. So the institutional quality will only increase with extra effort. We are not taking money away from the other institutions in our optimization we are only adding effort. This is idealistic but useful. Of course, the model could consider tradeoffs between effort in institutional quality where some effort is reduced in some areas and allocated to other areas.

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Webinar Q&A | Group Model Building Online

Webinar Q&A | Group Model Building Online

In 2020, when COVID-19 hit, a group of researchers from the University of Bergen found themselves stuck and could not run a planned in-person Group Model Building Workshop. They thought outside of the box and used Miro, a real-time collaboration platform to run the workshop online. They experienced several online activities and shared insights and ideas on how to do Systems Dynamics online with a group!

We had an insightful webinar with 180 attendees and the group could not only share what they have learned, but the participants did too. We had an engaging audience that made this webinar even better! Here are some questions from the Q&A session. Check the Recording, presentation, and Miro template.

ALL Seminar Series webinars are free for members of the System Dynamics Society. Learn More

Answers by:

Anaely Aguiar

Anaely Aguiar

Birgit Kopainsky

Birgit Kopainsky

Brooke Wilkerson

Brooke Wilkerson

Christina Gkini

Christina Gkini

Lars-Kristian Trellevik

Lars-Kristian Trellevik

Any attempts at asynchronous group model building?

No, we have so far only worked synchronously. However, A considerable number of seminar participants, however, did have experience with asynchronous group model building and reported on it during the discussion

 

How do you see virtual model building fitting in with in-person model building when we have that opportunity again? For example,  do you think that there is value in a two-stage event with one stage virtual and one in person (in either order)?

Online Group Model Building (GMB) has its pros and cons, and it is important to keep them in mind. One big advantage of online GMB is of course the amount of time, money, and not least carbon emissions that can be saved. With social dynamics and power relations being very important, a combination of the two – virtual and in-person once we have that opportunity again – seems like a perfect fit.

 

How much preparation time has this added to the process?

It is difficult to give a precise answer. For our very first online GMB workshop, we spent, in total, between two and three months for preparation. Some of this was not related to the workshop being online. Most of the preparation time was due to exploring the tools and functionality of the online platform, designing the board from scratch, and adjusting the scripts in parallel. It helped to have a person who dedicated time to this and then trained the rest of the team in no longer than a couple of hours. After the material has been developed, we had a couple of practice rounds to ensure the team is in sync. Now that we have done this several times there is hardly any extra preparation time.

 

How does the causal loop formation work in the group? What if people do not agree on connections?

This is, of course, a big challenge, but it is a challenge that is independent of the online versus in-person format of group model-building workshops. In our experience (both online and in-person), disagreements can usually be resolved by carefully breaking down the process in operational steps and by iterating a causal loop diagram and eventually a simulation model over several workshops.

 

How big a group do you think the online setup allows for? Is there a maximum number of participants?

This is a bit difficult to answer – it definitely depends on the scripts one chooses. For larger groups, we usually try to have more divergent activities where work done in smaller groups during the workshop. We have tried with multiple groups working in parallel and there was no platform-related issue.

 

Can you export data from the Miro board? Or import data into another software for data analysis purposes?      

You can export all contents of a Miro board either as images or in a pdf “booklet”. All data, however, need to be manually transferred to other software. For example, the behavior the participants identify in the Graphs Over Time are drawings, not data points, so they cannot be imported for any direct analysis. Similarly for the Causal Loop Diagram.

 

How can you protect the board so it can’t be messed up by some of the participants?

You can change the Sharing options at any point in time to withdraw editing rights from participants. There are numerous sharing options for both the Miro Team members (the core modeling team) and stakeholders who are usually invited through a link. For example, they can have editing rights, be able to only view the board, or have no access at all. This page provides some more information.

Another very helpful function is the ability to “lock” specific elements on the board. Elements that are locked cannot be moved unless they get “unlocked”. You can find more information here. In our case, we had locked all elements of the board except for the Graphs Over Time templates and the Action Ideas templates, both of which needed to be moved by the participants/team.

 

Did everyone have access to touch-sensitive devices/styluses?  Or were there setbacks in drawing BOTGs?

Most people drew the graphs with their mouse/touchpad. This might not allow for the most nicely drawn or very detailed graphs, but we were interested in broad trends so, in our experience, this worked fine. We didn’t observe any significant delays or received any questions around this part, although it might be a bit slower than drawing on paper, as is to be expected. Something that might have helped was that we had shared with the participants a short video on using the “pen” tool and that we asked them to use it in the Icebreaker as well.

 

When the participants are drawing the behavior over time charts, do you go through with each of the participants what each variable means? When I do GMB I find it tricky to balance the time between letting the participants explain the variable and getting a hold of the time.

Yes, we usually discuss behavior over time graphs in a round-robin fashion. But if time is very limited, we might not go through all the variables participants have identified. Instead, we ensure of course that participants share the same number of variables each.

 

To clarify: you had groups of people work together? Where these groups then physically together in one place but working online with other groups? Or how was the setup?

In the workshop we presented in the seminar, there were two independent groups on two separate Miro boards, each with their own modeling team (facilitator, modeler, stage manager, and note-taker). All participants were working from their own location individually and interacting only virtually with the rest of their group.

We have since run a workshop with participants in a group being physically together while the modeling team was online and found it quite challenging. In this case, however, there wasn’t any equipment set up that could potentially make the setting work (for example, microphone(s) in the room where members are physically present, or a projector for the Miro environment).

 

After the workshop, what content did you share with the participants?

We exported and shared the image of the Causal Loop area. In addition, participants still had the link to the Miro board with all the workshop activities.

 

There was stuff around the causal loop creation table on the Miro board. What was it and what was it for?

Around the Causal Loop frame, there is an overview of the script (left-side), and the elements for the Action Ideas script (right-side). The Action Ideas are not part of the process of developing the causal map and were not “in the view” when the group was working on it (in other words, the focus on the screen was on the Causal Loop frame).

 

I’d like to reinforce the tremendous opportunity that lies ahead. Over the past year, I suggest the world has been forced to jump ahead at least five years regarding on-line group meetings, etc.  Thanks for leading the way! We’ve only just begun!

Thank you. We couldn’t agree more. Going online opens up new opportunities. We just need to make sure that we do not introduce and/or reinforce digital inequality. This is, of course, easier said than done.

 

Why did you choose Miro and not Mural?

The honest answer is that we were not aware of Mural at the time so it wasn’t a very conscious decision! It seems to be quite similar so it could be a good alternative. However, what Mural seems to not offer is the built-in video conferencing that Miro allows. This can help, since participants are not simultaneously in two platforms, Miro and e.g. Zoom. The downside is that, at least until recently, Miro’s video conferencing did not offer a “gallery view” of the participants; that is, one cannot view all participants simultaneously. The other thing to note here is, for the stakeholders to be able to join the Miro video call, they need to have signed up to the platform in advance (anonymous users cannot participate in the video call).

 

Can you elaborate more on the role of the “stage manager” please? I’m curious to hear about the coordination and choreography before and during the workshop.

Absolutely! The first thing to say is that there was one common script with all three roles (facilitator, modeler, and stage manager) that was developed based on the facilitator’s experience with GMB and the “run-throughs” that one team went through. The script was quite detailed – as an example, when participants were sharing their Graphs Over Time, the script would describe something as:

“Facilitator asks for volunteer participants to share their favorite graph. Stage Manager Zooms in on the participant’s desk and the graph they describe. After the graph has been described, the Stage Manager zooms out. The facilitator informs that modeler will move the graph to the clustering area and the modeler does so. The facilitator asks for a second volunteer participant”

While perhaps a bit tedious to produce in this detail (it took us certainly two run-throughs of the entire workshop, already starting with a written facilitator script), it was very helpful for us to run our first workshop. Also of note, we did use a lot of Screen Sharing within Miro, hence the Stage Manager was mainly following the “action” to ensure the participants see what is relevant for the activity.

What was interesting during the workshop was that the participants asked on occasions the Stage Manager to show them some element that was out of view. With this, we mean that it seemed important to treat this role not as someone “going through the moves” but as someone the participants can interact with. The facilitator announcing the actions of the Stage Manager (e.g. <name> will now take us to the Overview of our next activity) and the Stage Manager asking the participants if the view is ok might have helped in this respect.

 

Are there other platforms besides Miro and Mural that you explored?

We would like to take this opportunity to acknowledge and thank all those who shared their own experiences with Online Systems Mapping. Here are some of the platforms that other seminar participants mentioned and/or had experience with:

Miro in combination with Zoom (also in breakout rooms); Video conferencing with shared Vensim screen; a combination of Padlet for pre-work and Loopy for a virtual workshop, in an asynchronous setting; Kumu; Mural; InsightMaker.

Definitely check this very insightful note in System Dynamics Review that Nici Zimmerman and her collaborators have published (Moving online: reflections from conducting systems dynamics workshops in virtual settings). As well as this webinar (Community Model Building – Drought) from iseesystems.

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