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How Did En-ROADS Get 755,000 users? Lessons on Modeling, Interface Design, and Facilitation

How Did En-ROADS Get 755,000 users? Lessons on Modeling, Interface Design, and Facilitation

Achieving widespread engagement is a significant challenge with a System Dynamics model. Yet, En-ROADS, the climate solutions simulator co-developed by Climate Interactive and MIT Sloan, has captivated hundreds of thousands of users globally. In this webinar led by Andrew Jones, John Sterman, and Florian Kapmeier, the team shared how their commitment to System Dynamics modeling principles, innovative interface design, and thoughtful facilitation created a global movement. The lessons learned are relevant for all System Dynamics modelers seeking to make a greater impact in their fields.

1. Modeling: Build Trust and Ensure Accuracy

“You have to have a rigorous, evidence-based model that is fully documented and tested every which way.” John Sterman

En-ROADS’ impact is built on a robust modeling foundation that adheres to rigorous standards of transparency and continuous testing. John Sterman underscores the importance of rigorous validation: “You have to have a rigorous, evidence-based model that is fully documented and tested every which way,” he states, highlighting the necessity for clear, accessible documentation that allows users to understand and trust the model’s operations.

The En-ROADS team enhances model reliability by calibrating past model behavior against historical data (by, e.g. Lazard, the IEA, etc.) and comparing future model behavior against the behavior of climate models used by the Intergovernmental Panel on Climate Change (IPCC), identifying discrepancies not only to prove correctness, but also to pinpoint areas needing improvement. Andrew Jones elaborates on this process: “We compare the model against historical data to understand where the discrepancies are and how we can improve. It’s not about proving the model’s correctness but about identifying areas for growth and improvement.”

For System Dynamics modelers looking to build confidence in the model, these practices are essential. Providing full transparency through comprehensive documentation and continuously validating models against industry benchmarks are crucial steps in establishing credibility. By adhering to these principles, modelers can ensure their models are technically robust and able to support decision-making.

2. Interface Design: Guide Users to Key Insights

“We designed the interface to lead a user to discover our modelers’ top insights without support.” Andrew Jones

En-ROADS’ interface is designed to ensure users reach key insights intuitively. Andrew emphasized the goal: “We designed the interface to lead a user to discover our modelers’ top insights without support.” The interface offers both a beginner mode for quick understanding and an advanced mode for users with more technical skills, providing detailed charts and additional assumptions. Dynamic visuals and animations transform static data into a narrative, making complex concepts accessible and engaging.

Within a few minutes exploring the En-ROADS interface, new users quickly grasp three critical insights:

  1.  “It’s still possible” – to bend the emissions curve and reduce average temperature increase.
  2. “There’s no silver bullet”, highlighting that no single solution can solve the climate crisis.
  3.  “Many solutions together”, emphasizing that combining multiple climate solutions is necessary to mitigate the climate crisis.

An interface designed around key insights helps users understand complexity. The ease of engaging with a new innovation—trialability—is crucial for initial adoption and fostering word of mouth. Yet, negative experiences can lead to adverse feedback, potentially stifling the adoption and diffusion of the model. Sterman emphasized: “if people try something and have a bad experience, they will generate unfavorable word of mouth that can squelch the adoption and diffusion of your model.”

John Sterman emphasizes the consequences of neglecting interface quality: “Suppose you have the world’s greatest model, but a terrible interface. Nobody learns anything, nothing will change, and you and everyone have wasted precious time and resources. That’s a failure mode.”  But he warns, “The opposite, though, is far more dangerous: a great interface with an underlying model that lacks integrity and hasn’t been carefully tested means you’re helping people learn things that are wrong and possibly downright harmful far more effectively than ever before.”

By focusing on intuitive design and rigorous validation, En-ROADS ensures that the simulation is insightful and reliable for understanding possible climate solutions. This strategy serves as a reference for those aiming at making their models both informative and influential. As a System Dynamics Modeler, which 2-3 key takeaways would you like users to learn from your model?

3. Facilitation: Create a Safe Space for Learning

Make sure that you create a safe room where participants can share and challenge their mental models to allow them to engage deeply and learn together.” – Florian Kapmeier

Facilitation is critical to En-ROADS’ global impact. Through experiences like the interactive En-ROADS Climate Workshop and the roleplaying game Climate Action Simulation Game, Climate Interactive effectively conveys the insights of the model by fostering environments that encourage deep learning and reflection. Florian Kapmeier emphasized the importance of these settings: “Make sure that you create a safe room where participants can share and challenge their mental models to allow them to engage deeply and learn together.” This approach allows participants to openly test their assumptions and understand the underlying dynamics of climate change.

Florian, referred to Andrew’s Top 10 Tips to Engage People with a System Dynamics Model,  highlighting one key aspect: By asking participants  to mentally the likely impact of a climate solution on the temperature before running a scenario in En-ROADS, participants reveal their existing mental models and learn more effectively by comparing their understanding with model results. “Learning happens when the theory of thinking is laid out and people have to make a choice.”

The commitment to creating a secure and open space for dialogue is foundational to the success of the engagements with En-ROADS. This facilitation strategy enhances the participants’ ability to understand complex concepts, and encourages them to apply these insights in practical and impactful ways. By ensuring that each session serves as a safe space for exploration and challenge, Climate Interactive fosters an environment where transformative learning and genuine understanding can occur.

Climate Action Simulation for IKEA, Australia

Community & Policy Engagement

Community building has been fundamental to extend En-ROADS’ reach globally. Thousands have completed the Mastering En-ROADS training program, which empowers facilitators to engage diverse audiences. The En-ROADS Climate Ambassador program further nurtures hundreds of facilitators who provide En-ROADS Workshops and Climate Action Simulations worldwide, ensuring a unified network of like-minded advocates. This well-structured support system ensures that these facilitators are equipped to spread their knowledge effectively, fostering a collaborative and impactful community.

In addition to training and support, Climate Interactive’s team emphasized the importance of engaging with policy makers, adapting communication to meet where they are in terms of climate change understanding. Presenting complex model data in an accessible manner is crucial for meaningful engagement. This strategy ensures that decision-makers receive information and are equipped to act on it.

The Power of System Dynamics

“System Dynamics is the most powerful way to engage other people in ways to improve system performance.” – John Sterman

The success of En-ROADS hinges on a commitment to the core principles of System Dynamics, paired with innovative interface design and effective facilitation strategies. This approach has educated a global audience on climate solutions and empowered them to act. John Sterman, reflecting on the broader implications, asserts, “System dynamics is the most powerful way to engage other people in ways to improve system performance”, underscoring the potential of System Dynamics to facilitate meaningful discussions and drive change across various domains.

Sterman reminded the audience that the discipline’s strength lies in its ability to convey complexity in a way that decision-makers can understand and act upon: “System Dynamics modelers need to invite people into the conversation, to join the collective effort and improve system performance together.” This collaborative spirit is reflected in the global network of facilitators, policymakers, and climate advocates brought together by En-ROADS.

As System Dynamics modelers, the challenge is to not only build robust models but also to design engaging interfaces, facilitate participatory workshops, and nurture a community of like-minded advocates. By doing so, modelers can extend their influence beyond their field and create meaningful change in the world.

Watch the recording below

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Solving Bottlenecks in Dairy Production Facilities with System Dynamics

EXECUTIVE Summary

  • FrieslandCampina faced potential bottlenecks in production due to the merging of two factories. They hired SD&Co which employed system dynamics simulation models to predict and manage these issues effectively, ensuring smooth operational integration.

  • The project led to strategic changes, such as optimizing algorithms for pallet selection and adding a conveyor belt system, thereby enhancing efficiency without the need for extensive physical expansion of facilities.

  • The implemented changes have prepared FrieslandCampina to handle increased production volumes and maintain efficiency even in scenarios of partial factory downtime, demonstrating a successful adaptation to the merger’s demands.

#FriedslandCampina #SD&Co #Diary #Netherlands

The Problem

FrieslandCampina, a Dutch cooperative, specializes in transforming milk from dairy farmers into a wide array of dairy products. They were undertaking a significant project: merging two of their production facilities. This merger was anticipated to introduce new challenges, particularly in the filling and palletizing stages, as well as in the operations of their fully automated warehouse. The project was handled by SD&Co and their primary goal was to foresee potential bottlenecks under various post-merger production scenarios. Identifying these potential bottlenecks was crucial to ensure a smooth transition and maintain efficiency. Additionally, SD&Co was tasked with devising strategies to address these bottlenecks in the most effective and efficient manner possible, keeping in mind the operational workflow and the increased scale of production due to the merger.

Figure 1 – FrieslandCampina’s production facility

The Solution

FrieslandCampina faced a significant challenge: implementing changes to their factory could take up to two years. This long time frame posed a risk of reduced production output or the possibility of overinvesting in capacity expansion. The complexity of the situation was heightened by the interconnected nature of the factory and warehouse processes, which made it challenging to accurately predict outcomes using traditional tools like spreadsheets.

To navigate these complexities, SD&Co employed a comprehensive approach by developing four distinct simulation models. Each model varied in scope and level of detail, enabling a thorough analysis of a wide range of production scenarios and potential physical modifications to both the factory and the warehouse. These simulations were instrumental in testing the effects of various changes and understanding their impact on the overall operations.

Thanks to these sophisticated simulation models, FrieslandCampina and its suppliers were able to pinpoint the most effective and efficient solutions. They could identify adjustments to the factory and warehouse that would best accommodate the increased volumes resulting from the merger of the factories. This strategic approach allowed for a well-informed decision-making process, ensuring that the adjustments made were optimally aligned with the new operational requirements.

Figure 2 – Examples of sectors of the system dynamics model developed by SD&Co.

Figure 3 – Overview of simulation dashboards.

Outcomes

In this pivotal project, SD&Co identified the most efficient modifications necessary for the factory and warehouse to handle the increased volumes post-merger. FrieslandCampina, in collaboration with its suppliers, is actively implementing these recommended changes. The key deliverables of this project were the innovative simulation models and a comprehensive presentation detailing the recommended changes. These system dynamics tools provided valuable insights, leading to strategic adjustments within the operational framework of FrieslandCampina. 

One significant change was the refinement of the algorithm that manages the selection of pallets for outbound elevators. This adjustment negated the need for physical expansion of the outbound elevators and staging lanes, thereby optimizing existing resources.

Additionally, they introduced a small conveyor belt behind two palletizers to avoid the need for a more extensive and costly redesign of the internal transport system around the palletizers.

Based on the simulation, FrieslandCampina also made a strategic decision to refrain from further investments.  The model demonstrated that the new capacity would be adequate across a variety of production scenarios. This included scenarios where parts of the factory might temporarily break down or require maintenance. The project’s outcomes have significantly contributed to the robustness and efficiency of FrieslandCampina’s operations. The implemented changes ensured that the factory and warehouse can smoothly handle increased volumes, while providing a buffer for unforeseen production challenges. 

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EXECUTIVE Summary

  • Product design is a specific form of complex innovation that touches all areas of an organization’s management. While entrepreneurs recognise the value of design, they often tend to focus on areas that customers recognise as important but that they are often already happy with. Helping entrepreneurs to systemically assess the benefits of spending on developing different aspects of the user experience is, hence, fundamental to increase the return over investment and to improve business sustainability.

  • To address this, the CzechInvest Agency developed an interactive board game powered by a System Dynamics model simulator that simulates the economic development of a company over six years and calculates the profitability of changes made to the product design.

  • Based on the game results, the Agency presents opportunities to improve product design. The company’s management can thus objectively identify weaknesses and chooses a strategy to design a better product that improves profits.

#CzechInvest #ProductDesign #Innovation #CzechRepublic

The Problem

Entrepreneurs face a multitude of challenges when it comes to product design, ranging from understanding user needs to navigating technical constraints. One of the primary hurdles is identifying and addressing the true pain points of their target audience. Without a deep understanding of user behavior, preferences, and expectations, entrepreneurs risk developing products that fail to resonate with their intended market.

Additionally, entrepreneurs often fail to understand the concept of product design focusing too much on a particular aspect of their product (often the way it looks) neglecting other aspects of it. While the product presentation is important it is only one part of product design and entrepreneurs need to have a holistic view of the product balancing user-centric design with technical feasibility and cost considerations. In short, entrepreneurs need to ensure that their product ideas are not only desirable but also manufacturable and economically feasible.

The Solution

The solution developed consists of a board game and a complementary System Dynamics model. The game covers five areas of innovation that players can decide to invest on, and the simulation model is used to estimate the performance of these investments. The five areas of innovation players can select by placing a card on the boardgame are: i) services (Služby) ii) Marketing methods, iii) Customer Relationships (Vztahy se zákazníky), iv) Goods and products (Zboží), and v) Internal Company Processes (Procesy).

Once the player has selected an area, the performance of the players decision is estimated using a System Dynamics model designed for this purpose. The figure shows an overview of the building blocks of the System Dynamics model and their links. A customer segment is a group of people or organizations that a company wants to attract and create value for through an appropriate value proposition. The larger the customer segment, the more customer relationships to manage and the busier the distribution channels. Every sale means billing, and billing is a source of revenue. Higher revenue means higher PROFIT for the company, thus growing key resources, one of which is the bank account. The more money in the bank account, the better it is to buy assets, hire new employees, increase product production capacity, and expand the distribution network.

The Design Value Algorithm (DVA) coefficient enters the model in the Customer Segment building block (see figure of the Stock and Flow diagram) and thus influences all other elements in the model. The input of the DVA coefficient to the Customer Segment can also be verified in the Business Algorithms in the Dynamic Business Model illustration.

The winner of the game can be determined either:
a)    by the evolution of PROFIT’s cumulative profit with other players.
b)    by looking at the impact of the design improvements made during the game.

Outcomes

CzechInvest clients implemented this solution and offers structured interviews to company management. The game demonstrates a systemic link between the concepts of design and user experience and quickly reveals the best strategy for further investment in product design.

Below there are some examples and comments from one of the customers that played the game:

Client Number 1X – XYZ Ltd:  “The measured value of design is the difference between the evolution of the PROFIT indicator that the company generates without investing in design (the blue curve in the graph) and the evolution of the profit that the company generates based on the decision to invest in design (the other three curves). The value of design is a dynamic indicator that changes over time.”

Interpretation for the client 1X – XYZ Ltd: “The company needs to invest in design; in this situation, where its average UX is 66%, it is profitable. “

According to the parameters given: the average UX (User Experience) = 0.66. This means that the company can still increase user experience by 34%. However, the manager did not make a strategic decision to earn more on design. Instead, he chose a strategy that is not in line with the company’s potential to increase UX. He placed investments in improving the functionality of the product first and investments in distribution third. In doing so, he identified the lowest UX sub-value in sales. If he wants to serve his customers better, he needs to strategically address sales first.

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The World Bank Uses System Dynamics to Identify Root Causes of Poverty

EXECUTIVE Summary

  • Madagascar has one of the highest poverty rates in the world. In 2022, an astonishingly three out of every four people in Madagascar lived below the poverty line.

  • Poverty has proven to be particularly resistant to previous policy interventions. Hence, the World Bank decided to turn toward system dynamics to identify the systemic causes of the problem.

  • Working with focus groups across the country, this project developed a causal loop diagram that clearly illustrated vicious cycles that stakeholders see as direct contributors to poverty. It allowed stakeholders to identify potential leverage points to develop anti-poverty programs in Madagascar.

#WorldBank #Poverty #Madagascar

The Problem

Poverty in Madagascar has remained persistently high and somehow complex, despite many attempts to reduce it through anti-poverty policies and interventions. As shown in the Macro Poverty Oulook, the share of the population living in poverty (US$2.15 in 2017 PPP) was 81.7% in 2020, 81% in 2021 and 80.6% in 2022.

One of the reasons why past anti-poverty policies have had less than desired success in reducing poverty is the limited understanding of its determinants. Empirical investigations of the determinants of poverty often use linear specifications that regress objective measures of poverty such as income or consumption against observable indicators theoretically justified to explain poverty.

To uncover the root-causes this analysis used a systems thinking approach to characterize a high-level, dynamic, and multi-dimensional view of the poverty trap with Causal Loop Diagrams (CLD) generated from focus group discussions in 6 provinces across the country.

The Solution

The World Bank organized a series of focus groups across a variety of diverse communities within judiciously selected communes in Madagascar. The aim was to identify, understand, and address the unique poverty challenges they face, and to enrich these findings with qualitative data. These focus groups were intentionally structured to spark discussions about the primary obstacles encountered by the communes. Insights from participants across different ages and genders were used to deconstruct these challenges into several root causes. Each root cause was further distilled into simpler, more comprehensible sub-causes.

The causes and their corresponding sub-causes were reanalyzed after deconstructing the poverty issues faced by each commune. This allowed for diligently examining the intricate interconnections that define these challenges. Special emphasis was given to understanding the interactions among various sub-causes and the overall impact on the system. Specifically, we identified reinforcing patterns or loops that sustain poverty and negate efforts by both individuals and policy interventions to alleviate it. In the end, insights shed light not only into the economic determinants of poverty but also the cultural, political, and behavioral intricacies across different demographics, including gender, age, occupation, and community type (rural/urban).

Analyzing poverty by amplifying the voices of the impoverished and evaluating qualitative data was influenced by a seminal World Bank book titled “Voices of the Poor: Crying out for Change.” This report harnessed focus groups across 23 countries to relay the experiences of the impoverished in their own words. In doing so, it underscored significant multidimensional aspects of well-being that had not been previously explored in conventional poverty analyses.

In addition to highlighting the voices of the impoverished and the crucial subtleties pertaining to their circumstances, this project incorporated systems thinking tools. This innovative approach enabled us to evaluate the qualitative data from the focus groups and discern the pivotal narratives and relationships explaining the perpetual cycle of poverty experienced by many households.

The Causal Loop Diagram is a partial representation of the multi-dimensional poverty trap from the perspective of urban households. The CLD identifies eight feedback loops representing the urban poverty trap that inhibits the group’s ability to:

  • secure high income livelihood opportunities (R1)

  • alleviate impact of cost of living (R2)

  • uplift socio-economic status (R3)

  • participate in decisions (R4)

  • develop resilience to shocks (R5)

  • mitigate increasing cost of business (R6)

  • mitigate shocks to business (R7)

  • enhance skills (R8)

Outcomes

Clearly addressing one or few sub-causes will not generate an overall change required in poverty trap situation.  The systems thinking exercise proposes a portfolio of upstream and downstream entry points and pathways to improve the ability of communities to move out of poverty over time. This will inform design of projects by the World Bank to activate the identified entry points.

In particular, the project resulted on a list of potential interventions that are directly linked to the feedback loops driving the system. For example, one of the potential interventions could be to promote business and entrepreneurship. Stakeholders in the focus groups thought that training, mentoring, infrastructure, and financing support could help circumvent the current low levels of business and economic activities (R1), and to diversify employment opportunities (R8).

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Fast-Track Cities Uses System Dynamics to Enhance HIV Care

EXECUTIVE Summary

  • Low levels of viral suppression at 69% for people with HIV make it hard to believe the 95% target level will be achieved by 2030 in St. Louis, USA.

  • As a solution, Fast-Track Cities-STL opted to use group model building means to 1) gain understanding of the fragmented service landscape and 2) to empower the community to address causes of health inequality.

  • The causal loop diagram revealed the importance of community-building for care engagement and created the foundation to build capacity by generating interest and commitment among participants. It also shed light on policies’ unintended consequences leading to service fragmentation and the need for rapid start programs to consider holistic social support for sustained care.

#Fast-Track Cities #HIV #Health #USA

The Problem

Levels of viral suppression at 69% for people living with HIV in St. Louis are far below the targeted goal of 95% required to end the HIV Epidemic in the City of St. Louis, U.S., by 2030.

To increase viral suppression, Fast-Track Cities- St. Louis created a subcommittee dedicated to expand access to rapid initiation of antiretroviral (ART) medication (also called Rapid Start) and to utilize a collaborative governance model to engage in consensus-oriented change. This initiative organized a series of group model building sessions, bringing together diverse stakeholders: those living with HIV, patient advocates, healthcare professionals, researchers, and policymakers. The objective of these sessions was threefold:

    1. To identify structural barriers affecting the adoption and accessibility of Rapid Start services in St. Louis.
    2.
To comprehend the varying perceptions and mental models of providers and clients concerning HIV diagnosis and treatment.
    3. To guide a standardized approach for implementing Rapid Start ART across different service providers.

Figure 1 – Behavior-over-time graph displaying the percentage of virally suppressed people receiving ART medication in the St. Louis region according to different outcome perceptions.

The Solution

The landscape of Rapid Start in St. Louis remains intricate. Despite three major healthcare providers rolling out rapid start programs, the data and insights from these initiatives have remained compartmentalized. Recognising this challenge, Fast-Track Cities-STL was compelled by the group model building approach as it offered an opportunity to map both the service provision landscape as well as important factors impacting quality HIV service while building capacity among communities. Fast-Track Cities-STL finds it incredibly important to utilize empowerment approaches to build a more agile, responsive public health HIV response.

Hence, the aim of Fast-Track Cities-STL was to use participatory group model building not only as means to uncover a greater understanding about the system of access to rapid start ART in the St. Louis region, but also to lay the groundwork for a grassroots community led collaborative in HIV care that aims at addressing the root causes of health inequities and outcomes. Fast-track Cities-STL anticipated that an interactive approach like group model building could help generate interest and community commitment in working on the solutions.

The resulting model combined insights from participatory GMB sessions involving those living with HIV in St. Louis, healthcare providers, and advocacy groups. The Causal Loop Diagram (CLD) crafted from this process comprised three reinforcing loops and eight feedback loops. Factors like mistrust, personal agency over health, peer support, and access to pivotal services emerged as the most influential determinants in the model’s behavior.

Figure 2 – The resulting CLD based on the GBM sessions.

Three fundamental feedback loops are highlighted. The “Problem of Delays” is a reinforcing loop where waiting for healthcare coverage causes individuals to lose their sense of control over their health. This diminished sense of control subsequently leads to decreased engagement within care spaces. Essentially, the longer the wait, the less control individuals feel, leading to even lesser engagement in care, creating a reinforcing cycle.

In the “Mistrust” balancing loop, experiences of racism and interpersonal stigma within the care system amplify mistrust. This heightened mistrust deters individuals from engaging with care, particularly in “non-peer-led groups.” As a result, they face a reduced risk of encountering cultural incompetency from providers. This loop underscores a critical insight: individuals who face racism and interpersonal stigma in care settings are more likely to disengage due to these negative experiences, balancing out their exposure to potential further harm.

The “Operation in Silos” balancing loop highlights how navigating care within bureaucratic silos makes individuals feel dehumanized, akin to “feeling like cattle.” This sentiment fosters greater mistrust, leading to decreased engagement in care. The more compartmentalized the care, the more individuals feel like mere numbers, leading to a balancing effect where they trust and engage less with the system.

Outcomes

The tangible outcome of the project was the CLD that participants developed and validated during the participatory group model building sessions. Key insights from the model revealed the importance of community-building opportunities for engagement in care, especially in the uptake of Rapid Start ART. The model also shed light on how some well-intentioned policies inadvertently led to service fragmentation and undermined the autonomy and peer support vital for those living with HIV. Furthermore, the model highlighted that the factors influencing the initiation of medication were intrinsically linked to the continuity of care. In essence, the model underscored the need for rapid start programs to holistically consider the social scaffolding essential for individuals to initiate and sustain care.

As aimed by the project, the Group Model Building approach also provided means to build capacity among communities disproportionately impacted by HIV and leverage their insights for system change. On the one hand, the insights offered by the model pointed out the importance of building community to generate engagement in care—including the uptake of Rapid Start ART.  On the other hand, the project stimulated interest among participants and recruited them to continue their engagement with the organization; several individuals expressed a commitment to continue working on the project beyond the exercise.

Regrettably, a major setback led to a leadership vacuum, halting the initiative. Nonetheless, a participating organization has taken the baton, advancing the rapid initiation of ART services.

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System Dynamics Unravels ICU Tensions at the Portuguese Oncology Institute

EXECUTIVE Summary

  • The Portuguese Oncology Institute (IPO) faced a critical challenge in its intensive care unit (ICU) where doctors and nurses experienced high turnover due to tensions with surgeons and limited resources, ultimately leading to a high death rate. Surgeons accused ICU staff of holding patients longer than necessary, leading to a backlog in surgeries. Despite utilizing external ICUs, the issue persisted.

  • Multicriteria and optimization approaches did not provide a solution. Only a System Dynamics approach using a management flight simulator enabled IPO’s leadership to understand the dynamics and discuss the causes and leverage points around the problem.

  • Based on the System Dynamics model, the IPO established 10 new beds in the appropriate care units leading to the resolution of tensions and decreased turnover and death rates in the ICU.

#IPO #PatientCare #Oncology #Health #Portugal

The Problem

Despite the demanding nature of the work in IPO’s intensive care unit (ICU), doctors and nurses were passionate about their roles. However, the turnover rate was high due to strained relationships with their colleagues. Surgeons, who would only schedule delicate surgeries when the ICU had availability, accused the ICU staff of unnecessarily prolonging patient stays and not vacating beds promptly. As a result, the ICU became a bottleneck, leading to a growing waiting list for surgeries. To address the issue, management began utilizing external ICUs, but this did not alleviate the resentment or reduce turnover. Figure 1 displays the growth of the quitting rate of the IPO’s ICU waiting list, which is the rate at which patients leave the waiting list without being admitted to the ICU for surgery. 

Figure 1 – Cumulative distribution of waiting list quitting rate

The ICU faced a high death rate, and care sharply declined when patients left for general wards, as readmission was rare due to bed shortages. To prevent readmission or premature deaths, the ICU kept patients until they were stable for general wards. Surgeons hesitated to operate on fragile cancer patients without available ICU beds. Despite being undersized, the ICU’s high cost per bed (equipment and staff) deterred expansion. IPO’s management hesitated to invest in ICU or intermediate care, as adjacent wards needed more beds for patients awaiting surgery. This compromised the organization’s performance.

The Solution

By employing the System Dynamics approach, stakeholders in the IPO’s ICU, including doctors, nurses, surgeons, and management, were able to gain valuable insights into the intricate interactions and dilemmas that existed. The approach provided a platform to examine the underlying causes of the tensions, identify the systemic drivers contributing to high turnover, and uncover the unintended consequences of certain actions. Figure 2 shows the causal loop diagram (CLD) that was developed along with the medical team and used to discuss the uses of a management flight simulator.

Figure 2 – CLD used for discussion with medical team

Through the use of the management flight simulator, stakeholders were able to witness the unfolding dynamics of the problem. This new understanding enabled IPO’s leadership to make informed decisions and take proactive steps to address the challenges. Figure 3 shows the core components of the System Dynamics model underlying the management flight simulator.

Figure 3 – Simulator core, showing the waiting list at the bottom

Outcomes

The application of the model had a significant impact on IPO’s management. As a result, a new Intensive and Intermediate Care Unit was established, reducing reliance on external ICUs and improving resource management. The ICU’s limited capacity and absence of intermediate care beds had previously led to high death rates and compromised patient care during the transition to general wards. Additionally, the practice of retaining patients in the ICU until they were fit for general wards caused delays in surgeries and increased costs.

With the opening of the new unit, equipped with 6 intensive care beds, 4 intermediate care beds, and 2 isolation rooms, these issues were effectively addressed. IPO’’s dependence on external ICUs was significantly reduced, leading to improved resource allocation within the organization. The expanded capacity and inclusion of intermediate care beds ensured smoother patient transitions and better continuity of care. Timely scheduling of surgeries enhanced efficiency and reduced costs while curbing death rates. The establishment of the Intensive and Intermediate Care Unit demonstrated IPO’s commitment to improving patient outcomes, resulting in a positive impact on both patient care and organizational performance.

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System Dynamics Helps Farmers Escape Poverty Trap in Guatemala

EXECUTIVE Summary

Guatemala holds the 4th highest global ranking for chronic malnutrition, and climate change is intensifying the challenges subsistence farmers face in providing food for their families. Utilizing a System Dynamics model facilitated meaningful discussions among various stakeholders and government entities, ultimately leading to the provision of strategic resources, such as livestock and expert guidance, for 152 families. This support enabled farmers to break free from the poverty trap and make valuable investments in their agricultural endeavors.

The System Dynamics model effectively illustrated the interplay between numerous variables, empowering farmers to comprehend and take control of key leverage points essential for their well-being and prosperity.

#Food security #Farmers #Agriculture #Guatemala

The Problem

Guatemala faces a staggering 55% prevalence of chronic malnutrition (a widely recognized indicator of food insecurity) in rural areas and ranks as 4th worst globally. Climate change is amplifying the difficulties subsistence farmers in Guatemala face in providing food for their families. Although climate change affects all food producers in various ways, subsistence farmers are especially vulnerable due to their limited access to irrigation and crop insurance, which could help mitigate the effects of fluctuating weather conditions. Furthermore, because subsistence farmers depend on their own production to feed themselves and their families, low yields and crop loss often result in malnutrition and starvation.

This underscores the need to understand how local farmers can collaborate and work with both local and central governments to enhance their food security.

The Solution

The model was developed using Group Model Building (GMB) and stakeholder engagement in two distinct communities. In each case, we collaborated with farmers and representatives from central and local governments to create causal loop diagrams that illustrated the primary relationships within their respective food systems and the variables influencing food security resilience in the face of climate change. This understanding was then converted into quantitative System Dynamics (SD) models, which facilitated discussions regarding potential policies.

The model comprises five main components:

  1. Maize local market: This component captures the primary dynamics of the local market using a traditional commodity model.

  2. Households: This element represents the dynamics affecting household cash availability and purchasing power, with revenues generated from maize production, livestock, and other activities.

  3. Livestock: This component illustrates the primary dynamics of livestock (specifically poultry) production on local farms.

  4. Soil: This part demonstrates the dynamics of organic nitrogen and organic carbon in the soil.

  5. Water and irrigation: This component captures the infrastructure used for irrigation and exogenous variables like rainfall.

The model features three main feedback loops:

  1. Commercial agriculture (R1): Revenue from maize increases household cash, which enhances their ability to invest in farming (such as seeds, fertilizers, and irrigation systems), resulting in improved soil quality and increased water uptake.

  2. Poverty trap (R2): A portion of maize production is allocated for self-consumption. The higher the proportion dedicated to self-consumption, the less maize is available for the market, which reduces revenue and subsequently investment in farming. Low investment in farming leads to low yields, further decreasing the amount of maize that can be sold.

  3. Reserves driving wellbeing (R3): Higher production rates result in more maize being available for self-consumption, reducing the need to spend money on purchasing food. This increases farmers’ available cash for investing in the next year’s harvest.

Outcomes

The policy recommendations from our study were utilized by local NGOs and government representatives to lobby their representatives in parliament and the Minister of Agriculture (MAGA). As suggested in the report, 152 families were provided with livestock in small quantities and supported by technical experts to develop small production farms.

This demonstrates the compelling nature of using System Dynamics in addressing complex issues, such as food security in the context of climate change. System Dynamics enabled to graphically represented the system through causal loop diagrams, providing a crucial visual aid that facilitated communication with local stakeholders in a way that other modeling approaches, mainly focused on mathematical formulations, could not achieve. Further, the emphasis on stocks in System Dynamics allowed for the effective representation of food stocks and key resources like soil organic matter, while maintaining model simplicity.

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Twinings Uses System Dynamics Games to Enhance HR Capability

“Realistic simulation is a powerful approach to building capability. The business simulation developed [by Dashboard Simulations and Lane4] gave [Twinings staff] an experience that called for them to develop and deploy competitive strateg[ies]. People learned a lot from the experience, and because [the experience] is their [own], the transfer to the workplace was easy. The same business simulation could be used over and over again with different groups within the company so the return on investment has been exceptionally good.”Simon Brocket, International Human Resources Director, Twinings

The Goal

Twinings is a leading global brand in the hot beverages market and offers a range of premium teas and malt beverages. In an effort to enhance the services offered to business partners, Simon Brocket, International Human Resources Director at Twinings, challenged Ken Thompson, of Dashboard Simulations, and Austin Swain, of Lane4, to design a business game that would help Twinings Human Resources (HR) staff understand the challenges of operating a country level business unit. The training sessions would be run over the course of a single day, and thus the insights had to be communicated in an engaging, authentic, and succinct manner. With that in mind, Ken and Austin chose System Dynamics to the power the simulator.

The Challenges

Historically Twinings business units are confronted with several challenges. In a series of interviews and workshops Ken and Austin worked with Simon and other Twinings subject matter experts to document their mental models and identify the most important challenges. Seven were selected for the simulator:

  • Price vs. demand
  • Reacting to the market vs. bucking the market
  • New customers vs. existing customers
  • Value chain vs. organizational health
  • Leading indicators vs. lagging indicators
  • Your strategy vs the unexpected
  • Me vs. us ­­ Working in an executive team

The Simulator

As business units address these challenges the decisions they make ultimately affect customer loyalty as measured by consumption. The System Dynamics model at the core of the simulator represents this using stocks and flows as shown in Figure 1 below:

Tea1Figure 1: Model overview

In this model, customers move from stock to stock via the blue flow arrows. As customers progress from left to right, they consume more products leading to higher revenues. At each stage consumers can also choose to leave, hence the goal of the game is to make decisions which:

  1. attract new customers, turn them into regular consumers and ultimately vocal fans
  2. prevent customers from moving to lower levels of consumption or switching to competing products altogether.

Diving In…

During the daylong session, HR staff were organized into groups representing country level business units. Twice during each simulated year, the teams were given the opportunity to review results and make decisions for the upcoming period. At the end of each year the business units would present their results, insights, and plans for the following year to a senior Twinings executive acting as Group CEO.

As the game progressed teams explored each of the seven challenges; identifying insights and highlighting new options and strategies. Here are a few of the challenges they experienced.

Leading Indicators vs. Lagging Indicators

As prior decisions played out in the model, several metrics were reported on the decision board shown in Figure 2 below.

Tea2Figure 2: Decision board

Leading non-­financial indicators like growth rate and lagging financial resultswere identified and discussed. As a result, HR staff gained a personal understanding of the information country level business units have to assess progress and make decisions, and how those decisions can affect future results.

Your Strategy vs. the Unexpected

With the start of every round the facilitators would announce market updates such as “a key competitor has changed their prices,” or “There is a shortage of raw materials” and tweak the model accordingly. With this new information and the metrics from their individual decision boards the business units were then faced with the decision: “Do we keep to the original plan or adjust to the new market conditions?” Teams made their decisions independently and the simulation moved forward. As the results came in the teams learned if the decision was wise, they discussed insights and planned changes.

Me vs. Us ‐‐ Working in an Executive Team

Each business unit, as in the real world, was comprised of several members that formed an executive team for that region. Over the course of the day­long session, critical skills of leadership, communication, collaboration, and decision making under pressure were tested and improved and the concept of collective responsibility was deeply reinforced.

The Impact

To date, the game has been run for eighteen different groups at Twinings, with very positive feedback. Staff have come away with personal exposure to the challenges facing the business  units they serve, resulting in strategies and insights to serve them better.

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RSC Uses System Dynamics to Increase HVACR Sales Against the Tide

“Using the proven Strategy Dynamic process focused our limited resources on organizing strategic issues, identifying the critical resources, and developing the insight to more rapidly create intuitive and actionable business strategy.”Warren Farr, CEO, Refrigeration Sales Corporation

System Dynamic’s benefits do not have to be driven by outside consulting efforts.  Sometimes, internal education and training lead to insights which cause a company to thrive and even evolve during the most tumultuous times. Take Refrigeration Sales Corp  (RSC), during the downturn of the late 2000s. CEO-turned-modeler, Warren Farr, was able to see RSC’s revenue go up 25% in a market that saw sales go through a  25% decline, thanks to forecasts driven by SD modeling and insights gained during the process of developing those models.

RSC is a third generation privately owned family business located in Ohio, USA specializing in wholesale sales and support of Heating, Ventilation, AC and Refrigeration (HVACR) units.  Over the years the company had expanded its business beyond just equipment sales to credit lending, technical support and training for many thousands of statewide contractors.  At the time the HVACR industry itself had enjoyed three decades of continuous growth, and RSC had seen annual AC sales increases averaging 10%. But for the first time in years, these annual sales rates were decreasing. Competitors, and the company’s own customers, believed this to be a “temporary lull” caused by the economy as a whole and, along with more cautious suppliers, most parties were optimistic for the future. However, Warren, who had just taken the first of several courses in System Dynamics, believed that recent trends in 2001 signaled a new phase in the market’s development and that this historic growth would inevitably slow down more permanently.

Applying System Dynamics

Inspired by the notion of feedback stemming from inside the system rather than external causes, Warren applied the SD methodology to create long-term market forecasts; ones which were crucial to a company whose sales and profits were tied directly to the fortunes of market volume.  Working off of the three views of the future in the figure below, Warren sought to find the underlying truth of the industry. While suppliers and customers were sticking with the “hope” prediction, and the company’s management was preparing for the “best guess”, information on the market’s installed base showed clearly that the “fear” scenario was in fact the appropriate response to prepare for.

A key systemic insight is this. The nature of durable goods, is that they are, well, durable.HVAC2Sales levels for a durable product have the shape of a bell curve; sales of new units increase until the market becomes saturated, at which point new sales are mostly replacement or upgrades. Warren’s competitors and customers were blind to this basic truth, and fully expected demand to start rising again with the next recovery in the economy and in construction.

This saturation effect is simple enough to state – but how significant would it be, and over what time-scale would it play out? The dynamic model quantified the accumulation of the installed-base and internalized the feedback of declining first-time sales, allowing managers to observe reality playing out and refine their intuitions about the ebbs and flows of the industry’s growth cycle.

Not only was the approaching saturation point reducing the installation base for new AC units, but in a northern U.S. region like Ohio where an AC unit could last for 15 to 20 years, replacement sales were unlikely to fuel growth either. The model was predicting a 20% to 30% contraction in sustainable annual unit sales, which would be considered catastrophic in most markets.

U.S. Regulations Delay Market Contraction

The reaction to these insights was swift and not without controversy.  In the years 2004 and 2005, sales spiked even higher than the hopeful prediction thanks to new US Dept. of Energy regulations which were causing contractors to stock up on older AC units before new minimum efficiency requirements took place and raised prices.  But RSC stuck to its forecasting model. In an industry which had known nothing but growth for decades, RSC was downsizing its workforce, tightening customer credit limits and consolidating its inventory and warehouses.  Both suppliers and customers thought these actions were short-sighted according to common industry logic and current record sales.  But RSC’s uncommon logic would swiftly prove itself as the predicted market contraction came true.  After 2005, sales entered an unprecedented crash, setting the market average back down to 1994 levels.

“The modeling provided a longer-term perspective, allowing RSC management to make these dramatic changes in company bandwidth over a period of about 3 years, avoiding the excess cost associated with rapid ‘cutting’.” Warren Farr, CEO, Refrigeration Sales Corporation

Forecasting Leads to Market Share Growth

Thanks to their SD forecasting efforts, RSC changes were proactive and planned, and not reactive with unintended consequences. Though RSC would have survived the industry downturn without modeling, the company  was now in a prime position to diversify and take on new market share as competitors sought to shed expenses in a bid to stay afloat.  New talents, territories, and market shares were taken from unprepared firms scrambling to adapt to the crash. In territories where the AC market saw a 30% contraction from 2000 to 2010, RSC saw a 25% increase in annual revenues and 30% increase in its sales locations.

RSC’s story highlights a number of points. First, managers need to regularly ‘step outside’ the day-to-day crush of business activity, and understand the fundamentals of what is happening in the market around them. Second, just being aware of principles – like market saturation – may not be enough. Often what is needed is modeling work to figure out the quantified, time-based consequences of these dynamics. Third, the company’s work highlights the advantage of making decisions with forethought and examination, rather than waiting for the impact of new market conditions to throw off business plans. The story reflects the simple but powerful insights that System Dynamics can bring to such questions. Clearly, RSC’s strategic change decision was very significant, enabling them to create new advantages over the competition.

Lastly, we can see that System Dynamics is not some highly technical tool only accessible to math whizzes, but a practical, accessible method that smart managers like CEO Warren Farr can learn to use to great effect.

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Achieving a Polio-Free World Through System Dynamics Simulation

EXECUTIVE Summary

This System Dynamics model underpinned a 192 country resolution to eradicate polio globally and led the Bill and Melinda Gates Foundation to give Rotary International $100 million to fund the polio eradication effort.

The model made a case for continued funding policy eradication by providing compelling evidence that polio outbreaks will cost more than continued intense vaccination. While the reduction in the incidence of cases was making it look like the cost of immunization was exceeding its benefits, this application of System Dynamics shows that dealing with ongoing, long-term sporadic outbreaks resulting from stopping or slowing down immunization programs is even more costly than dealing with sporadic outbreaks.  The process resulted in a simulation model that estimates the costs of two alternative policies. Option 1 was to continue efforts to eradicate polio and option 2 was to reduce the immunization rate and deal with sporadic outbreaks.

This analysis came at a critical time. In February 2007, the WHO Director-General, Dr. Margaret Chan, convened an urgent stakeholder consultation to discuss the option of switching from eradication to control. Clearly showing the dynamics and giving the wavering commitment a name helped key stakeholders appreciate the options quantitatively and with a much longer time horizon. Since then, efforts have continued to focus on finding the resources needed for complete eradication and on dealing with the other complex challenges that remain. With the support of the simulation model, national and global health leaders and financial supporters re-committed to completing eradication, which led to several hundreds of millions of dollars of resources.

#Polio #WHO #Vaccination #Health

The Problem

Following the successful eradication of smallpox and impressive progress in the elimination of polio in the Americas, in 1988 the World Health Assembly committed to the global eradication of wild polioviruses by the year 2000. By 2000, the Global Polio Eradication Initiative (GPEI) had significantly reduced the global circulation of wild polioviruses. However, in 2002–3, faced with insufficient funding to continue intense vaccination everywhere, the GPEI focused its vaccination efforts. At the time, wild polioviruses continued to circulate in six countries, but many other countries remained vulnerable to importation. Political and logistical challenges led to outbreaks and exportations, and between 2004 and 2006 wild polioviruses appeared again in previously polio-free African and Asian countries.

Toward the end of 2005, a debate began about abandoning the goal of eradication. How could the world continue to justify the significant use of resources (both financial and human) on polio, particularly with the number of cases globally already so low and so many other disease control and health services programs in need of resources?

The Solution

The dynamic disease outbreak model represents a more complicated version of the standard SIR model used in a popular System Dynamics textbook (Sterman, 2000). However, in Polio, we must deal with different types of imperfect immunity (i.e., from historic or recent exposure to polioviruses – including the oral poliovirus vaccine and/or vaccination with the inactivated poliovirus vaccine – as well as a latent period and routine or supplemental immunization rates). Modifying and expanding our existing model allowed us to determine that it was not possible to “effectively control” (i.e., achieve low cases) at a low cost. This means that control either implies high costs and low cases, or low costs and high cases, but not low costs and low cases.

Stock an Flow Diagram

However, our most significant insight came from exploring the dynamics of the economic investment in eradication. After watching the GPEI deal with the reintroductions of wild polioviruses in previously polio-free countries between 2004 and 2006, we recognized that reducing vaccination led the stock of susceptible individuals to build up and ultimately to outbreaks after some delay. Responding to the outbreaks requires reinvesting in intensive vaccination, which after some delay contains the outbreak and reduces or eliminates the circulation of the virus. With success comes a perception that the high level of investment compared to the low incidence is no longer justified. If policymakers succumb to the resulting pressure to reduce vaccination spending, this creates a situation in which populations again become vulnerable to new outbreaks.

“If policymakers succumb to the resulting pressure to reduce vaccination spending, this creates a situation in which populations again become vulnerable to new outbreaks.”

To capture this behavior, we constructed the negative feedback loop shown here, which we called  “wavering”. We incorporated this feedback loop into our dynamic disease model and tailored the model to two populous northern Indian states in which wild poliovirus still circulates. We explored two options: (1) vaccinate intensively until eradication;  and (2) vaccinate intensively only if the costs per incident case remain below a certain acceptable level, but reduce the vaccination intensity otherwise  (i.e.,  a “control” option with the possibility of wavering).

Causal Loop Diagram Polio
Simulation Chart Polio

Outcomes

This application of System Dynamics highlights the systemic causes of overruns and emphasizes the importance of understanding the complex physical and social systems within which large projects operate. We, fortunately, saw the wavering commitment loop when no one else seemed to see it, and we went beyond just seeing the loop to build and use a model that provided answers to critical questions at the time the decision makers could use them (and needed them and asked us). In the presentation to the stakeholders, we showed the results to tell the dynamic story in the simplest possible way (i.e., by comparing a firm commitment to a wavering commitment showing the cumulative costs and cases).

We did not focus on explaining the model itself to attempt to walk the decision makers through the equations or diagrams. Instead, we focused on communicating the key insights based on what they already knew (e.g., the 2002–3 reduction in vaccination led to big outbreaks and high costs). However, we anticipated and received (as anticipated) some criticism from economists who did not recognize in the model a traditional health economic analysis, but these were relatively limited.

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