193

Education for Sustainable Development:
A Systems Thinking Approach
Chris SODERQUIST1 and Susan OVERAKKER2*
1

Pontifex Consulting, 11 Sargent Street, Hanover, NH 03755, United States of America
2
New Earth, 22 Trafton Street, York, ME 03909, United States of America*e-mail: sustainablesusan@gmail.com

Abstract
The challenges of sustainability are adaptive challenges, and require the development of more effective
mental models that support a transition to sustainability. Our ability to generate effective mental models ishampered by common deficient ways of thinking – and this deficiency is often shared by policymakers,
private sector leaders and the general population. In this paper we provide an overview of these deficiencies
and how systems thinking could provide the framework to answer to these challenges. We propose a set ofskills, a visual language and technologies to increase our ability to learn systems thinking. Finally, we provide
an overview of several educational initiatives currently showing promise at developing a sustainability-focused systems thinking capacity, as well as recommendations for additional educational approaches.
Key words: adaptive challenges, mental models, systems thinking, sustainability

1. Introduction
The complexity of challenges facing humanity today
is growing exponentially. We are reaching the limits ofthe exponential growth model we have experienced sinceat least the Industrial Revolution. There is indisputableevidence that we must transform the systems that are
responsible for overshooting our planet’s limits, forexample, those that are responsible for global emissions
and impending climate catastrophe. Still, we see little
global or national support for requisite policies. The
combined challenge of addressing short-term objectives
coupled with weak institutions of global governancemakes formulating positive outcomes tough, especiallywhen multiple issues such as security, prosperity or
implementation of universal values still present a challenge. Available information is vast, confusing and often
inconsistent or too complicated, making bottom-up action difficult.
We suggest that education for sustainable development is essential for creating needed change. It will
facilitate a transformation to a more harmonious worldthat is developed taking into account inspiration fromsome principles of nature. Since we need to influencemultiple “systems of systems,” we present a frameworkof Systems Thinking as an essential element of education.
Systems Thinking provides principles and methods
through which practitioners intervene in and learn about
real world problem situations in order to bring about
constructive change.
Global Environmental Research
14/2010: 193-202
printed in Japan

2. Sustainability Challenges and Our Mental
Models
2.1 One cause of intractability: Sustainability
challenges are adaptive challenges
Sustainable development challenges are far fromroutine – we suggest they are adaptive challenges(Heifetz & Linsky, 2002).
Technical (routine) challenges are common, but notnecessarily simple: routine means there is a known solution/protocol to follow in order to resolve them. Running
low on copy paper is a routine or technical challenge
because we have a procedure for restocking. Physicians,
when diagnosing a patient with brain cancer, have a rangeof treatments including surgery. This example is far froma “simple fix.” However, there is an established protocol
for diagnosing and treating brain cancer.
Conversely, an adaptive challenge is a situation
without an established protocol or procedure. Achieving
global sustainability is the ultimate adaptive challenge.
There is no single, unified, generic way to transition
communities, regions or the planet toward a resilient,thriving future. What that future holds will be unique foreach community – yet must be tied into the larger context.
Each community will have its own culture, set of physical assets, resident skills, and desired future. The ability
to think and communicate systemically will be an important capacity a community must have or develop inorder to make the transition. In the absence of such ability,
efforts may focus on low (or no) leverage activities and©2010 AIRIES194

C. SODERQUIST & S. OVERAKKER

they may lack coordinated and orchestrated sets ofinitiatives.
2.2 Adaptive challenges require fundamentally
modifying our mental models
Determining our current sets of routines, protocols
and technical solutions are mental models. Mental
models are the set of assumptions we use – often unconscious, untested, implicit and incomplete – to make senseout of the world. We have mental models about ourfamilies, organizations, the global market, the environment and of course, what is sustainability is and how toachieve it. We use our mental models to assess what ishappening, predict what might happen and choose how to
influence our future.
Our mental models are frequently useful, or each of us
would not have lived to our current age, nor would wehave survived as a species (e.g., our mental models are
responsible for the institutions and systems we’ve developed as humankind.) However, our mental models
appear inadequate to address today’s adaptive challenges.
All seem intractable. If mental models determine how weobserve the world and take action, there must be something wrong with the mental models we apply to intractable, adaptive challenges.
Richmond and his colleagues at isee systems, theproducers of the STELLA software, use a simple thought
experiment called Mature Trees or its business equivalent
Rookie-Pro to make the point that even when shown a setof six assumptions about what’s basically a supply chain
problem, over 75% will fail to correctly mentally simulate the implications of those assumptions – how thesystem will react to a simple, single shock – even thoughthese assumptions are far simpler than what you would
observe in the real world (Richmond, 2001). The system
is simpler than reality and the majority still gets it wrong.
The implications are staggering, because if most of us
cannot determine how a simple system will behave in the
future without an intervention, how could we possibly
know how a more complex system will behave if we try
something to improve it?
An example
Our increasing economic activity currently leads toconsuming natural resources at rates beyond their ability
to regenerate (remain sustainable). To address this issue,
many countries adopt an official policy to reduce theintensity of consumption while continuing to promote
growth in GDP. Assuming each unit of GDP is responsible for consuming a specific amount of the resource:
reducing the intensity means reducing the amount ofconsumption per unit of GDP.
There is a stock and flow map (Fig. 1) showing two
reinforcing loops: one responsible for regenerating a
resource and the other driving GDP growth. The flat line
assumes the resource renews at 5% a year with no GDP
growth: GDP is 1,000 and the annual amount of consumption per unit of GDP is 50. The steep decline curve
assumes GDP grows 3% annually.

Fig. 1 Example of poor mental models: the relationship between
GDP and consumption of a renewable resource.
Visualization using the mapping language of Systems
Thinking: if the amount of GDP (the stock or rectangle) is
growing with a reinforcing loop (R2), then the annual unitof resource consumed per GDP must decrease at roughly
the same rate that GDP increases, which is a rapid anddramatic reduction. Reducing GHG emissions intensity
while continuing to expect yearly exponential growth of
GDP requires similar assumptions about dramatic(unrealistic) reduction of intensity.

Assuming that such growth is desirable, one way tokeep the resource from running out is to reduce theintensity (consumption per unit of GDP). When asked
how much this intensity should be reduced, many believethat a 20%-50% reduction in intensity would be sufficient. In fact, in this example, to ensure the resource is
not depleted requires reducing intensity by 90% over 40
years!
Reducing greenhouse gas emissions intensity while
continuing to expect yearly exponential GDP growthrequires similar assumptions about a dramatic(unrealistic) reduction of intensity.
2.3 Our mental models are often inadequate due toseveral well-established “ways of thinking”
As demonstrated in the policy example of GDP and
the intensity of resource use, we sometimes have great
difficulty in developing useful mental models. Specifi-

Education for Sustainable Development: A Systems Thinking Approach

195

cally, people have several “ways of thinking” that lead topoor, ineffective mental models.
Common “ways of thinking”
In our mental models we tend to:1) Focus on events instead of patterns (apply boundaries
which are too narrow),2) Apply spatial boundaries which are too narrow, as
well,3) Underestimate (ignore) inherent time delays,
4) Assume one-way causality (instead of feedback
loops),
5) Avoid or skip simulating potential unintended consequences to our actions, and
6) Exclude non-physical realities.
Below we provide additional details on these common ways of thinking.
2.3.1 Focus on events instead of patterns (temporalboundaries too narrow)
From an early age individuals are taught to focus on
events, usually something occurring right in front of them,in space and time. The ability to hyper-focus on the
predator that has just leapt from the bushes and to act
immediately has served humankind well. What distinguishes the human species from other animals is ourability to see patterns and make predictions. It is thishigher level of cognition that must be utilized in today’s
world, but it is something we must increase our ability to
do effectively.
However, events often lead people to engage in reactive behavior while ignoring the historical background orseries of events over time. What is needed is the skill touse events to stimulate long-term, “over time” thinking.
Climate change could become recognized as a threat
when weather events such as rising temperatures, rainfall
or drought are seen in trends occurring over multiple
years, or rather decennia. The rising impacts of industrialized farming could become apparent when over theyears an increasing amount of animal-related influenzas
strike.
Determining to what extent an organization iswell-managed depends on the timeframe of the performance measures applied by management. Applying alonger time boundary often leads to better mental models
regarding cause and effect and how to act. In Fig. 2, as thetime frame expands, the management team is more likely
to see the “commodity cycle” nature of their business andgenerate systemic solutions rather than reactive,
cost-cutting policies.
Having temporal boundaries too narrow can haveserious consequences. People tend to extrapolate thefuture from the present, or from a persistently too narrow
time frame. All economic bubbles occur as a result of
this: if housing prices are rising now and have done so forthe past few years, we tend to believe they will continue
to rise. If prices for oil have been falling, we believe they
will continue to fall. One of the most significant assumptions that underpin much of our current economy isFig. 2 Dynamic thinking: applying an “over time” perspective.
Different timeframes might be used by management. The
actions these leaders might take will be dramaticallydifferent based upon which of the three perspectives theychoose. With perspective 2, management would be“searching for those responsible.” Adopting perspective 3
would lead to “understanding industry dynamics and how
can we adjust our organization.” The power of adopting apattern-of-event perspective is transformative in guiding
the strategies chosen by an organization’s leaders.

the belief that continued exponential growth within aworld of physical limits is possible or even desirable.
“It makes sense that economies should follow rules
analogous to those that govern biological systems. [...]
But economists generally don’t see things this way, [...]
because most current economic theories were formulated
during an anomalous historical period of sustained
growth. Economists are merely generalizing from theirexperience: They can point to decades of steady growthin the recent past, and they simply project that experience
into the future” (Heinberg, 2010, p.5).
2.3.2 Underestimate (ignore) inherent time delays
Even when applying an “over time” lens, humans
tend to mentally simulate time delays poorly. Sterman
and Sweeney (2002) have demonstrated that a majorityof subjects (students at MIT) cannot predict how long it
will take for a decrease in carbon emissions rates to impact global climate temperatures, even when the assumptions are made very explicit. Ignoring time delays isa major inhibitor to understanding potential “worse
before better” scenarios when implementing public policies or organizational improvements. Public sector
managers avoid – and rightfully so due to the public’s
understanding of dynamics – policies that might eventually improve situations if they know that in the short term
they will contribute to worsening conditions (Soderquist,
2003). In many cases, decisions made today may takeyears before they have a desirable impact on the organization or system.
2.3.3 Apply spatial boundaries that are too narrow
We also miscalculate how the impacts of our actions
spread over time, and are often unaware of how they
impact across spatial dimensions. As the housing crisis

196

C. SODERQUIST & S. OVERAKKER

began to unfold, it became quite clear that due to theinterconnected nature of the global economy, the UnitedStates housing bubble and subsequent collapse was able
to impact economies all around the world. In theenvironment, emissions in China now impact the western
United States– just as years ago it became understoodthat pollution from the Midwest was damaging ecosystems in New England.
2.3.4 Assume one-way causality (instead of feedback
loops)We also prefer creating a linear cause-and-effect theory to explain behavior. When asked the question, what
creates a highly desirable country (Fig. 3), most people
generate a one-way causality list. A desirable country
occurs with good leadership, a skilled workforce,technology investments, a robust economy, strong
education, effective public services, strong security andshared values Fig. 3(a).
However, reality includes feedback. As shown in theFig. 3(b), technology certainly improves both educationand security; It is also true that both of these sponsor andfund technology improvements. Skilled workers supporta healthy economy, and a healthy economy provides
more funding to educate a more skilled workforce.
2.3.5 Avoid or skip simulating potential unintended
consequences to our actions“To fix this problem, all we have to do is X – no problem!” states a policymaker. After a few experiences of
the consequences of “no problem,” the public becomes
more cynical in the future. This is because we havelearned reality is filled with unintended consequences(and very few “no problems”). Unintended consequences
often result from overlooking important feedback loops.
In the Simplistic Mental Model about increasing farm
profitability, a balancing (B) loop works to keep
profitability high (Fig. 4). If profits decrease, then the
farmer increases fertilizer use (lbs/acre/year) and thus

(a)

(b)

Fig. 3 What causes a country to be desirable?
(a) Typical list-based, linear mental
model and (b) one demonstratingclosed loop relationships, feedback
loops.

Fig. 4 Understanding unintended consequences of agricultural commodity systems:
increased fertilizer use increases fertilizer in the water system – which come around to depress
profitability through public pressure to increase taxes. The vicious cycle gets set in motion: low
profits lead to increased fertilizer use, which lead to lower profits – and then more fertilizer use. Usinga mapping approach helps anticipate and avoid problematic unintended consequences.

Education for Sustainable Development: A Systems Thinking Approachincrease production per acre per year (the “o” means thatas profits drop, fertilizer use goes in the opposite direction – up). Profits increase as more sales leads to more
revenue for the same number of acres (assuming, ofcourse, that the additional cost of fertilizer does not outweigh the increased revenue per acre).
However, often unintended consequences accompany
increased fertilizer use. In the more Sophisticated Mental
Model picture, another loop is activated: increased
fertilizer use increases fertilizer in the water system –which come around to depress profitability throughpublic pressure to increase taxes. The “R” indicates it is areinforcing loop, meaning that it tends to go in the direction it is already going. In this case, the unintended
consequence is that a vicious cycle gets set in motion:
low profits lead to increased fertilizer use, which leads tolower profits – and then more fertilizer use (Sustainability Institute, 2003).
Using a mapping approach (e.g., stock/flow maps or
causal loop diagrams like shown here) will help anticipate and avoid problematic unintended consequences.
2.3.6 Exclude non-physical “realities”
In finding solutions to improve how systems behave,our formal models usually only include the things we canmeasure – we usually exclude “soft” variables likemotivation, trust, knowledge and skills. Many disciplines,
due to their mathematical and statistical nature tend toignore these types of variables, even though most people
will recognize that we already use (if only implicitly)
these types of variables in decision-making. Managers
know that these variables matter. Yet, they will often
leave them out of the formal model used to describe
organizational performance. From practice we know thatenvironmental laws require public support to be effective.
Therefore, using a mere “technical” or “legalistic” model
for analyzing the environmental law’s effectiveness,while leaving out the public’s perception thereof, is notuseful. This is why more recent management approaches(e.g., the balanced scorecard) include variables such as
morale, employee skills, and customer satisfaction.
Public policy models need to include not only technicalunderstanding of “the science,” but also public perceptions and knowledge – the human dynamics components
required for effective engagement and implementation ofpolicy.

197• Technologies.
When integrated into an overall framework, these can
improve our ability to collaboratively surface and improve our mental models in a way that will help us better
understand the world, and act more effectively in it.
3.1 Process
The systems thinking process (Fig. 5) applies ascientific method-based approach to building, communicating and applying understanding. Applying this processensures we have enough confidence that our conclusions
are credible and that any recommendations will beefficacious.
3.2 Set of skills
Richmond (2010) proposes a set of skills, that build
our capacity to be better systems thinkers (what he often
referred to as Systems Citizens), by addressing theinadequate “ways of thinking/being” described above.
Additionally, the following skills (further defined inFig. 6) support the process above:1) Dynamic Thinking,2) 10,000 Meter Thinking,3) System-as-Cause Thinking,4) Operational Thinking,5) Feedback Loop Thinking,6) Scientific Thinking,7) Generic Thinking, and
8) Empathic Thinking.
3.3 Technologies
Unfortunately, we have difficulty learning systems
skills when the impacts of our current “way of thinking”
fall outside the narrow range of our experience. We cannot improve performance when we cannot link ouractions to outcomes. Moreover we are just not good atmental simulation when the issues are dynamically complex – as adaptive challenges always are. For that reason,
we need mental exercise equipment and training regimes
to build our Systems Thinking skills. The technologies
found to be effective are:1) Stock and flow mapping: An operational mapping
language to improve mental simulation;

3. Systems Thinking: An Integrated
Framework for Collaboratively Building
and Communicating More Effective Mental
ModelsPrevious sections suggest that the elements of
Systems Thinking can significantly enhance the capacity
to develop and utilize mental models that can address theadaptive challenges we face. Specifically, Systems
Thinking includes the following:• Processes,• Sets of skills, andFig. 5 The process of building and communicating ‘Systems’
understanding.

198

C. SODERQUIST & S. OVERAKKER

Fig. 6 Developing more useful mental models using systems thinking is accomplished by applying several
Systems Thinking skills (Richmond, 2010).

Fig. 7 The case of diabetes: operational mapping language
improves mental simulation.

2) Computer simulation: Individual and collective
mental exercise equipment to build mental simulation
capacity; and
3) Microworlds and learning environments: Practicefields to generate profound shifts in thinking.
3.3.1 Stock and flow mapping: An operational mapping
language to improve mental simulation
As shown in the example of GDP and the intensity ofresource use, using a visual language that distinguishes
between stock (conditions) and flows (activities) in asystem helps to improve our ability to see time delays andfeedback loops – and thus improves our mental simula-tion capacity. Over time, as we develop proficiency inthis language, we simultaneously increase our Systems
Thinking capacity. However, just learning the language isinsufficient: we need additional tools to supplement ourmental simulation capacity as exemplified by Fig. 7.
In Fig. 7, the United States Congress requested theCenter for Disease Control and Prevention to reduce thenumber of deaths resulting from diabetes complications.
Specifically, it was requested to:a) Reduce the prevalence of diabetes;b) Increase the rate of screening to detect diabetes;
andc) Reduce the annual incidence of diabetes-related
mortality.
On the surface, these may seem like a perfect set ofgoals to address the diabetes epidemic in the UnitedStates. However, after developing a stock and flow map
to represent these assumptions, it became clear that thegoals were incongruent. Increasing the rate of screening
will detect the Undiagnosed Prevalence (of diabetes) andtherefore increase the Diagnosed Prevalence (of reported
diabetes). Worse, the number of people who die fromdiagnosed diabetes will also increase because new cases
have been added to the stock of Diagnosed Prevalence.
The goals are incongruent – impossible to achieve
simultaneously. This example demonstrates the value ofusing an operational, visual language to map out public
policy interventions in order to better mentally simulate
their efficacy.
3.3.2 Computer simulation: Individual and collective
mental exercise equipment to build mental
simulation capacity
Having an operational, visual language is a necessary
condition to improving the quality of our mental models.
However, it is far from sufficient. Even if we can visually
map the operational assumptions, individuals will havedramatically different mental simulations of thoseassumptions. This is illustrated in the following example.

Education for Sustainable Development: A Systems Thinking Approach

HIV/AIDS policies and impacts
The stated goal behind many strategies to address the
HIV/AIDS crisis is to ensure the fewest number of people
will ultimately die from complications associated withthe disease. In most cases, there are established programswith the expressed objective to provide life-extending
pharmaceutical therapies. (In some cases, due to socialand religious cultural stigmas, pharmaceutical treatments
are the primary or only intervention.) On the surface,these would seem to hold promise in achieving theobjective of reducing the total long-term mortality
resulting from HIV/AIDS-related causes. But will they?
After developing an operational map (Fig. 8) tovisualize the underlying structure of the epidemic’s
spread – with people moving from the Safe Population to
the Risky Behavior Population to the Infected Population– it is easy to see where pharmaceutical policies will
impact. They will slow the flow out of the stock of the
Infected Population. What happens if the survival timeincreases?
Although initially the trend is improved over a basecase (the straight line), over time more people die fromthe disease. This occurs because initially fewer people
leave the Infected Population stock. However, this increases the number of becoming infected...and more
become infected. Ultimately, even though it takes longer,
those people die and the volume flowing out (through199

dying) is even greater (line that eventually increases
above the straight line) than under the base case.
Many people do not see this as the logical implications of the assumptions shown above. This is why computer simulation is often required. We are usually good at
sketching assumptions, but have difficulty mentally
simulating their implications. Computer simulation
addresses this difficulty, and can improve mental
simulation capacity.
Any strategies focusing solely on reducing the deathsof the currently infected could have the unintended
consequence of creating more deaths – trying to be
humane leads to more suffering. The best way to reduce
deaths in the long term is to focus upstream and prevent
people from entering the Infected Population stock in thefirst place. It’s not that treatment shouldn’t be done – itmust be in order to reduce the suffering of those with thecondition. However, without some upstream focus –prevention – short-term efforts to reduce suffering anddeaths will backfire as more people will get the disease.
3.3.3 Microworlds and learning environments: Practicefields to generate profound shifts in thinking
Just as computer simulation can supplement, andimprove on, our mental simulation of Systems Thinking
maps, microworlds and learning environments canincrease the effectiveness of simulation-based learning.

Fig. 8 A systems approach to total long-term mortality resulting from HIV/AIDs-relatedcauses.
Becoming infected and starting risky behaviors are reinforcing loops. Slowing
the rate of dying initially accumulates more Infected Population and ultimately
the rate of dying increases.

200

C. SODERQUIST & S. OVERAKKER

These tools become practice fields that facilitate deepreflection on deeply held assumptions about the systems
we are trying to improve.
As an example, a learning environment was developed by the Darden School of Business at the Universityof Virginia, Pontifex Consulting, and the Sustainability
Institute for MBAs and undergraduates to deepen theirunderstanding of the structural causes of commodity
dynamics. Working as individuals and teams, throughrepeated experimentation by applying cycles of hypothesis/test/reflection, these students achieve a systemic
understanding of the shrimp fishery and commodity
systems in general. They are able viscerally to understandthe Tragedy of the Commons, a systems archetype that
occurs when stakeholders within a system are “harvesting” a commons – a resource shared by all. Individual
incentives to maximize individual short-term profits inthe system drive these stakeholders to overharvest in thelong term.
3.4 Technologies – Summary
The operational mapping language (of stocks andflows), computer simulation, and learning environments/microworlds form a suite of powerful technologies
for building Systems Thinking capacity.

4. A Critical Review: Perspectives on Possible
Limitations
System Thinking as defined in this article comes fromthe field of system dynamics, and is one of several approaches attempting to apply a “systems framework” forimproving social and environmental systems. There areseveral critiques of an approach based on system
dynamics; some of the major critiques being
1) Intensity of time/resources,
2) The focus on theory and process instead of practice and action, and3) Ignorance of social consequences.
4.1 Intensity of time/resources
Applying a Systems Thinking approach takes time.
With complexity of issues accelerating, it can seem as if
there is not sufficient time to apply Systems Thinking.
Additionally, according to Jackson (1991) Systems
Thinking has difficulty dealing with unanticipatedoccurrences during an investigation.
We agree that Systems Thinking reflection requires
more time than typically seems available for problem-solving. However, one common “systems archetype” is “Fixes That Fail,” which results from applying a
fix that has unintended consequences. Adequate systems
reflection could better anticipate such consequences.
The inherent danger in taking this time is of course,that the problem situation may worsen or evolve into
other situations. By taking sufficient time and reevaluating during specific stages of the analysis, thetemptation to short cut the analysis and miss out on
important developments can be minimized.

4.2 Weakness in the process of issue generation
Systems Thinking analysis requires first identifying
an issue for which to map, analyze and explore. Other
systems approaches (e.g., soft systems) emphasize thatlack of agreement on an issue within the system is part ofthe system, and include explicit practices for mapping/resolving such disagreements. (Lane & Olivia,
1994).
We recognize this as a limitation for certain problems
or situations. Employing a more collaborative approach
to Systems Thinking analysis can improve this agreementon the issue.
4.3 Ignorance of social consequences
Desired ends can only be achieved when social
consequences are taken into account. A critique ofSystems Thinking is that these social consequences suchas power and conflict are seen as irrelevant and are often
ignored (Lane & Olivia, 1994).
We agree that including assumptions concerning
human rationality in a Systems Thinking analysis ischallenging and has been described by others as realistic
challenges in decision-making (Simon, 1957).
Numerous approaches at blending systems analyses(e.g., combining soft systems with system dynamics)
have been proposed and by doing so, there is a potential
to increase the likelihood that social concerns will not be
overlooked (Salerno et al., 2008).

5. Current Educational Initiatives to Build
and Apply Systems Thinking for
Sustainable Development
In order to increase the likelihood that policies willachieve a lasting impact on adaptive sustainable
development challenges, public policy institutions, theprivate sector and all “global” citizens must develop theirsystems thinking capacity. Otherwise, it will be
extremely difficult to generate higher leverage solutions
supporting sustainability.
Described below are some current efforts in each ofthese spheres, as well as some suggested initiatives thatmight also facilitate movement toward a more sustainable future. They focus on different areas of society:• Government and Public Policy Education,• Private Sector Education,• Youth Education, and• Cross-sectoral approaches.
Not all are focused explicitly on sustainable development. Most programs focus on a subset of Systems
Thinking skills, not the full range, and utilize several
different delivery mechanisms: from face-to-face toonline or distance-based learning.
5.1 Government and public policy education
5.1.1 Georgia Health Policy Center – legislator healthcertificate program
In 2008, the Georgia Health Policy Center (GHPC)
developed and implemented an innovative state Legisla-

Education for Sustainable Development: A Systems Thinking Approach

tor Health Certificate Program (LHCP). The purpose wasto develop the capacity of leaders in both the state Houseand Senate to understand health content in ways that
promoted systemic thinking and led to more sustainable
health policy in the future. The program includes several“core content” sessions (e.g., health status, financing)plus additional “topical” sessions (e.g., childhood obesity,
trauma). During each session, legislators learn Systems
Thinking concepts and apply them to the session’s content through small group and large group discussion.
Legislators use such tools as:• a systemic framework for systems analysis of healthpolicy,• stock and flow maps, and• learning labs, for example, on childhood obesity.
To date, the GHPC has successfully graduated twocohorts. They are currently developing additional training for those cohorts, while preparing for a third cohort.
The childhood obesity learning lab has been used in themaking of legislation. A final indicator of their success isthe request of other states for GHPC to assist them indeveloping similar programs.
5.1.2 Sustainability Challenge Foundation
The Sustainability Challenge Foundation, located in
the Netherlands designed the International Programmeon the Management of Sustainability (IPMS), attracting
individuals from around the world to focus on conflict
management and to discover common interests behindthe perceived from the outset contrasting demands of
economic development and environmental protection.
5.2 Private sector education
Several private sector organizations have included
some form of the concepts presented here in theirleadership and management training courses. Some MBA& Sustainability programs also embed Systems Thinking
training in degree programs or executive education. Twoof the more notable executive education programs are run
by MIT’s Sloan School of Management and the University of Virginia’s Darden School of Business.
5.3 Youth education
Notable organizations and initiatives are working to
educate youth in the concepts of Systems Thinking andsustainability. Some examples include:• Cloud Institute,• K-12 System Dynamics in Education Project,• The Waters Foundation, and• Creative Learning Exchange.
5.3.1 US-China systems science learning project
The Vermont Commons School developed a relationship with Jiangsu Province’s Nanjing Educational
Technology Center, the education technology hub serving all secondary schools in the capital city. Over thecourse of three years, the Vermont Commons School andits project partners collaborated with Nanjing area
schools to co-create Systems Science curricula and case201

studies in most core school subjects, which were documented within a web-based workspace. This project
included several of the Systems Thinking organizations
listed above, including The Waters Foundation and theCreative Learning Exchange.
5.4 Cross-sectoral education
Some of the more promising approaches apply across-sectoral approach. Several examples are presented
in The Necessary Revolution (Senge, 2008). A few
unique programs are described here.
5.4.1 Energy for Sustainable Development Policy
Dialogue
The Energy for Sustainable Development Policy
Dialogue is a capacity building activity of the Energy for
Sustainable Development Initiative. Their key purpose isto promote active dialogue and exchange of ideas/options
aimed at addressing key challenges related to energy forsustainable development. All stakeholders in the energy
and development challenge are brought together in an
online course to focus on a specific topic. Although not
expressly developing the range of Systems Thinking
skills presented here, the Dialogue does greatly enhance
the capacity of Empathic Thinking.
5.4.2 Donella Meadows Leadership Fellows Program
The Donella Meadows Leadership Fellows Program
has accelerated the shift to global sustainability byincreasing the effectiveness of well-positioned sustainability leaders. Fellows learn to address social, economicand environmental issues at their root causes while
benefiting from a national and international network oftalented and supportive colleagues. Skills included are:
• Skillful learning within complex economic, social,and environmental systems, and• Acting effectively in change processes involving
multiple stakeholders with diverse goals and needs.
To develop these abilities, Fellows receive training,coaching and practice in Systems Thinking, reflective
conversation and visioning.
The Fellows Program nurtures these qualities in a
selected group over two-year cycles in on-the-groundprojects. At present the Fellows Network consists of 74
sustainability Fellows and practitioners from 16 countries.
5.4.3 Sustainable Food Lab
The Sustainable Food Lab is a partnership among
governments, NGOs and private sector organizations
responsible for the production and distribution of foodaround the globe. Their efforts are program-focused (e.g.,coffee supply chain) and while working on any program,participants learn and apply Systems Thinking concepts
to develop deeper understanding of why the systems
behave in ways they wish to change and where leverage
points are for improving that behavior.

202

C. SODERQUIST & S. OVERAKKER

5.5 Recommendations
Each of the initiatives and programs mentioned above
have successfully advanced the ability of participants tobuild and apply Systems Thinking to public policy challenges and in most cases associated with sustainable
development. Programs showing the greatest impact on
motivation and learning appear to be those that provide
the concepts in conjunction with an issue of particularconcern to participants. To that end, it is recommended
that additional effort be made to develop training
materials that can be delivered to groups already grappling with a sustainable development challenge, inparticular regional sustainability. With enhanced Systems
Thinking capacity, coordinated efforts such as Transition
Towns or The Natural Step planning process (or any regional planning initiatives) can have tremendous impact
on sustainability. The issues are at a scale that is both
visible and manageable, and the stakeholders have thecapacity to meet and engage in effective processes. Suchgroups would find that the tools described in this article
would facilitate engagement in developing actionable,
coordinated strategies.

6. Conclusion
This article presents the challenges we face in moving
to the next level of sustainable development – meeting
adaptive challenges requires learning “new ways ofthinking.” What is needed is an increased capacity tobuild and apply systemic understanding of the nature of
the systems we are trying to improve. Systems Thinking
provides a process, a set of thinking skills and technologies that can improve our ability to develop that systemic
understanding. Systems Thinking is often considered too
time-intensive or over-theoretical, not focusing on action
and lacking usefulness in real-world problem situations.
Systems Thinking certainly should not be overromanticized or seen as a theory that does provide thesolution to every existing complex problem. It has proven,however, to be a rich and varied discipline and aninvaluable tool to gain insights into complex problems
and provide action-oriented solutions to adaptive challenges we face in global, national and local problem
situations. Several local and international initiatives are
currently working to build that capacity in various societal sectors. We recommend that more coordinated efforts
to build Systems Thinking capacity be integrated into
firmly established, inter-connected regional initiatives(e.g., Transition Towns) to increase the effectiveness of
those initiatives and to spread more quickly through thesocial fabric. The time to undertake this challenge is now.
References
Heifetz, R. and M. Linski (2002) Leadership on the Line: Staying
Alive through the Dangers of Leading, Harvard Business School
Publishing, Boston.
Heinberg, R. (2010) Beyond the Limits to Growth, Post Carbon
Reader, Post Carbon Institute.

Jackson, M. C. (1991). Systems Methodology for the Management
Sciences, Plenum, New York.
Lane, D and R. Olivia (1994). The Greater Whole: Toward a
Synthesis of SD and SSM. 1994 International System Dynamics
Conference.
Richmond, R. (2001) An Introduction to Systems Thinking,
Hanover, New Hampshire.
Richmond, B. (2010) The Thinking in Systems Thinking: Eight
Critical Skills, Tracing Connections, ISEE systems and theCreative Learning Exchange.
Salerno F. et al. (2008) Concept Maps for Combining Hard andSoft System Thinking in the Management of Socio-Ecosystems,
Proceedings of the third international conference on concept
mapping.
Senge, P. (2008) The Necessary Revolution, Doubleday, New York.
Simon, H. (1957) Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations, 2nd ed.,Macmillan.
Soderquist, C. (2003) Facilitative modeling: Using small models togenerate big insights. The Systems Thinker, Pegasus Communications.
Sterman, J.D. and L.B. Sweeney (2002) Cloudy skies: Assessing
public understanding of global warming. System Dynamics
Review, 18 (2): 207-240.
Sustainability Institute (2003) Commodity systems challenges:
moving sustainability into the mainstream of natural resource
economies. A Sustainability Institute Report, Hartland, Vermont.

Chris SODERQUISTChris Soderquist has over 15 years experience as asystem dynamics consultant and trainer, with adiverse set of clients from the private and public
sectors. He is a guest lecturer at the Darden Schoolof Business (University of Virginia) in their
Executive Education Program, and on the Boeing
Engineering Leadership Program’s development team. He is a contributing
author to The Change Handbook (Berrett-Koehler, 1999) and delivers
system dynamics webinars for isee systems, where he is a consulting
partner.
Chris’s most recent focus areas include public health and environmental
policy, NGO strategic planning, and local community-based sustainability
efforts. Additionally, his research interests include linking dynamic
modeling with dashboard/scorecard development, implementation, andmonitoring. Some of Chris’s clients include: The World Economic Forum,
The World Bank, UNDP, State of Georgia, State of Vermont, Centers for
Disease Control and Prevention, The Boeing Company, Hewlett-Packard,
and Nissan.

Susan OVERAKKER
Susan Overakker is Program Coordinator at New
Earth, helping to achieve sustainable development
on a global level. Susan has worked for Dana
Meadows’ Sustainability Institute and has years ofexperience as Policy Advisor in the International
Office for climate change and energy of the Dutch
Ministry of Housing, Spatial Planning and the Environment and theMinistry of Transport, Public Works and Water Management. In addition to
her work, she runs her own website as ‘Sustainable Susan’ to inspire people
making steps towards a world in harmony. Susan believes that a journey ofa thousand miles begins with a single step, in which education and full
information stand at the basis.

(Received 20 September 2010, Accepted 24 December 2010)