What People Mean By “We Are Systems Thinkers”

I have been meeting lots of people lately who talk about being “systems thinkers.”  As a person who has played in the field of system dynamics and systems thinking for two dozen years, I get excited when people self-describe as playing in the same space.  To me “systems thinking” refers to classical definitions of a system and of systems thinking, such as:

System.  “A system is a set of interrelated elements.” — Russell Ackoff, 1971

Systems Thinking.  “The ability to see the world as a complex system.” — John Sterman, 2000

I have also started to listen more carefully to what people mean about what they say and what evidence they use to show what they mean.  With this listening, it seems to me that people are actually saying very different things about themselves, often with the same terms.  I have heard three very different things that people mean when they say, “systems thinking.”

Focus on systemic structures.  By systems thinking, some people mean that they focus on systemic structures.  They primarily focus on their own node, their own system, within a larger system.  They use processes like causal diagrams, rich pictures, and systems archetypes to describe their part of the system, its causes, and what they can do about it.  You can find hundreds of examples here, where I too have published.  This focus on systemic structures that are very close to their own node in the larger system seems to correlate with what I have observed to be segregating design, where everyone in the larger system tends to focus on their own local dynamics, irrespective of what others in the system are thinking or doing.

Focus on systemic decision structures.  By systems thinking, other people mean that they focus on a set of interrelated decision structures.  They primarily focus on how the decisions influencing their own node are influenced by multiple stakeholders who are each making decisions about their own nodes.  They use quantitative modeling processes like system dynamics (see my dengue modeling) and qualitative strategic modeling processes like my own GRASP and Strategic Clarity  processes, often coupled with the “systemic structures” processes described above.  With these processes, they try to see the whole, how each stakeholder contributes to causes of the problem, and how to partner around what each stakeholder could do to shift the behavior of the whole system.  This focus on systemic decision structures around their own nodes and those of related stakeholders seems to correlate with what I see as flocking design, where people and groups within a larger system pay attention to each other, reacting to each other’s movements, with the focus still primarily on one’s own resilience.

Focus on systemic agreement structures.  By systems thinking, yet other people mean that they focus on both the underlying and surface-level structures of agreements that determine the systemic decision structures.  They primarily focus on how deeper structures of embedded agreements influence the system of decisions that each stakeholder consciously or unconsciously accepts in their interactions within a system.  They use processes of co-hosting collaboration to decide together what their deeper shared purpose is within the stakeholders of a larger system, seeing what the requisite unique contributions are from each stakeholder, and together developing creative possibilities that they then leverage and tangibilize together, using processes like the Harmonic Vibrancy Move Process.  This focus on systemic agreement structures seems to correlate with what I observe to be uniting design, where people come together to redefine the underlying agreements that shape their system, the experience they have, the outcomes they achieve, and the resilience of the impacts they achieve.

So, the next time someone tells you they are a systems thinker, I invite you to perk up your ears, listen a little closer, and ask questions.  Look for the evidence of what they actually mean.  Are they focusing on (1) systemic structures to improve segregating designs, (2) systemic decision structures to support flocking designs, or (3) systemic agreement structures to co-develop uniting designs?  Those few moments of extra inquiry and evidence gathering might tell you a lot about what they actually mean.

From a Theory of Change to a Theory of Impact Resilience

More and more people are looking to large-scale social change processes to leverage their impact around very complex issues.  From poverty, health, education, epidemics, and inequity to water, air, green building, and renewable energy.  Scaling collective impact is everywhere.  I have been looking at, and engaging with many of these efforts, for two decades now.  In trying to figure out how to support large-scale change, many groups are trying to become evermore strategic.  As a big proponent of strategic clarity, I encourage the strategic dialog, and I encourage pathways that will support a group in getting to greater clarity about what they can do together and what will work.

In their strategic development processes, many groups now focus on developing a “theory of change.”  I agree that it is far easier to learn and refine a strategy when you have a theory of what you are going to do. And, I see some inherent difficulties in the way many groups currently frame their theory of change.  Hopefully a brief picture will clarify what I see as the intention and a better answer.

To start with, I see that most social-change efforts grow up around an effort that initially worked.  There was an intervention and there was an impact.  While not quite sure how it worked, the impact is there.  We created a kitchen, and more people were fed tonight.  In this experience, there is typically an implicit theory of “it just works.”  We do this, and we see the impact.  Usually the distance in time and space between the intervention and the impact is very low or immediate.  We can see it directly.  I see this as the lower-left quadrant in the 2×2 matrix below, low clarity of causality with a linear direction of causality.

Theory of Impact Resilience graphic for blog 032116a.001

This success often leads to the desire to scale the work, to get much greater impact.  To scale up the intervention often requires investment of greater capital.  Investors of this greater capital usually want to see a greater understanding of how the intervention will lead to the means that will drive the impact.  Greater investment wants to lower the risk of not understanding.  They want to see a theory of “change,” a “comprehensive description and illustration of how and why a desired change is expected to happen in a particular context.”  As far as I can tell, from what I see in foundation, nonprofit, and network reports and in my own conversations, most of these theories of change provide linear descriptions of how an intervention will lead to some specific means of change in a specific context that will lead to the desired social impact.  A to B to C.  I see this as the lower-right quadrant in the 2×2 matrix above, high clarity of causality with a linear direction of causality.  While this greater clarity of causality makes it much easier for the intervention leaders and the funders to test whether the intervention leads to the expected means and impacts, this linear approach to complex social issues leaves out a critical reality–feedback.

If the decisions you make today affect the decisions you can make tomorrow, then there is feedback.  A to C to A.  If the decisions you make influence others who then influence you, there is feedback.  All complex social issues contain impacts of any intervention on other stakeholders and on resources that influence the ability to continue to intervene in the future.  They all have feedback.

As the complexity of an intervention increases, like trying to feed a whole city through a large network of kitchens, most efforts seem to try to continue what they were doing before with just a lot more resources.  They use the same logic, on a bigger scale.  Lots of intervention, mixed with lots of magic, leads to lots of impact; so goes the “theory of I think.”  I think that if we just …  I see this as the upper-left quadrant in the 2×2 matrix above, low clarity of causality with a feedback direction of causality.  While the situation might be much more complex, with many more stakeholders and resources involved, I think if we just do a lot more, we will get much more impact.  It rarely works, often because of the unseen feedback effects, which is why social impact investors have moved more and more towards wanting to see something that demonstrates a greater clarity of causality.  Right now the best-in-class practice seems to be the “theory of change” I mentioned earlier.

To complete the high-level overview a theory of change provides, of the preconditions, pathways, and interventions needed to achieve the desired impact, many groups develop a complementary logic model and evaluation plan.  The logic model lays out a linear model of how the planned work with resource inputs and activities leads to the suggested outputs, outcomes, and eventual impact.  A very clean and relatively simple way to explain how to implement the theory of change.  The evaluation plan then provides measures to test the hypotheses for the different elements: the resource inputs; the activities; the outputs; the outcomes; and the impacts.  The strategy process then pulls together the theory of change, the logic model, and the evaluation plan, in a crisp, linear mapping.

Now, if (1) the social issues we face require much greater investment, influencing a greater number of stakeholders, in contexts of much greater feedback, and (2) a linear strategy based on a theory of change, logic model, and evaluation plan falls short of dealing with the feedback complexity, what do I suggest?  A “theory of impact resilience.” While a theory of change focuses on how a change in an intervention will lead to a change in specific means, which will drive change in a specific social impact–in a linear model–a theory of impact resilience looks at the system of causes, effects, feedback, and stakeholders that lead some interventions to generate a much more resilient system that delivers much greater, sustained impact.  I see this as the upper-right quadrant in the 2×2 matrix above, high clarity of causality with a feedback direction of causality.

Over the past twenty years, with many colleagues around the globe, we have developed systems-based strategic approaches to engaging multiple stakeholders around complex social issues.  There is now a whole industry of such approaches.  It turns out that it is not hard to bring together many people who are passionate about any specific social issue, find out how they each contribute different elements of the solution, and how they can work together to change the behavior of the whole system.  In the past decade alone, people have applied this kind of approach successfully on six continents to hundreds of important, complex social issues.  It only takes the will to do it, a little know-how and a few elapsed months of work.  Not decades.

So, while I applaud the desire of social impact investors to dramatically increase the clarity of causality between an intervention and a social impact, it is time that we move beyond “keep it simple,” linear models of causality to incorporate multi-stakeholder, feedback models of causality.  A theory of impact resilience, based on systemic, strategic approaches suggests how.  It provides a systemic theory, it lays out the systemic logic of how the interventions lead to shifts in the system of stakeholder responses and subsequent systemic impacts, and it provides an impact resilience scorecard of the systemic measures that indicate how the interventions are leading to systemic shifts, to greater resilience, and to scaling of the impacts.

A Framework for Achieving Clarity for You and Your Organization

Past-cast Series — Seeing relevance in earlier publications

Ritchie-Dunham, James. 2004. A Framework for Achieving Clarity for You and Your Organization, The Systems Thinker, 15(7), September, 7-8.

One of the keys to to being effective is to understand the complexity of your organization, what it seeks to achieve, and how you can contribute to that objective.  Through a series of exercises, you can gain clarity about these elements.  With an integrated understanding of what values drive the system’s behavior, how the parts of the system function, and how the values and parts relate, you will be much clearer in how your day-to-day actions will help you achieve the desired results for your area and organization.