Systems thinking examines how elements within a system influence each other and looks at relationships, patterns, and root causes rather than isolated problems. The iceberg model shows that most of an iceberg's mass is underwater and influences its above-water behavior, just as underlying factors greatly influence global issues. Stocks represent system conditions while flows are activities that change stock levels; intervening close to events has less leverage than addressing underlying factors. Mental models and assumptions must be challenged through tools like simulations to test theories and identify more effective solutions.

1. Conceptual Thinking

3.  Systems thinking is a way of approaching problems that asks how
various elements within a system — which could be an ecosystem, an
organization, or something more dispersed such as a supply chain —
influence one another. Rather than reacting to individual problems that
arise, a systems thinker will ask about relationships to other activities
within the system, look for patterns over time, and seek root causes.
 One systems thinking model that is helpful for understanding global
issues is the iceberg model. We know that an iceberg has only 10
percent of its total mass above the water while 90 percent is
underwater. But that 90 percent is what the ocean currents act on, and
what creates the iceberg’s behavior at its tip. Global issues can be
viewed in this same way. Download the Iceberg Exercise here.

4.  In the language of “stocks and flows,” events are stocks or system
conditions that we often seek to improve. Because they exist at a point
in time, we can usually see them. They are strong signals. But when we
intervene at or very close to an event, we are intervening at a place
within the system that has the least leverage. Take, for example, the
high proportion of New York City high school graduates who enter
CUNY schools and who require remediation in literacy and math. The
Center for the Urban Future calculated that 74 percent of incoming
students place into remediation, and roughly one-third fail the math and
writing proficiency exams. All of which suggests that the interventions
that we’ve put into place to help students graduate from high school do
not sufficiently deepen the skill sets students need to be successful in
college.

5.  Just below the waterline of our iceberg lie patterns of recurring events;
of the invisible iceberg they are the easiest to expose. Events occur
over time and thus are by definition “flows.” Flows are activities that
change the level of stocks. Longitudinal data, behavior-over-time
graphs, and stock-and-flow maps are forms of data that tell us
something important about a system’s behavior such as its stability or
volatility at certain moments. Patterns help us determine whether
growth is sustainable or when our growth potential is nearing its ceiling.
These types of data allow us to forecast or anticipate future events and
to shed light on whether or not our interventions altered outcomes.

6.  Think of the parable of the seven blind mice. When the mice
approach the elephant individually, they perceive only a part.
When you understand that you’ve got an elephant in front of you,
and not a fan, or a tree, or a snake, you’re in the position to make
coherent, appropriate and strategic decisions about what to do
next. As I noted in a previous post, we approach system redesign
from what we want to happen (for example, having a clear vision
of the attributes of a high performing school) not just what we do
not want to see happen (i.e., identifying an attendance problem
and redesigning only to eliminate that one problem.)

7.  A wonderful example of system redesign can be found in the book and
movie Moneyball (also referenced by Viktor Mayer-Schonberger and
Kenneth Cukier, authors of Big Data). Billy Beane, the general manager
for the resource-poor Oakland As, understood that trying to solve
problems (such as losing star players and needing to replace them) the
same way that the resource-rich New York Yankees would, was not
feasible. Beane understood that you had to radically redesign the team
using an entirely different set of data points and analytic methods. With
the right data points, from multiple different angles, and a different
mindset, he redefined how baseball teams are designed.

8.  A wonderful example of system redesign can be found in the book and
movie Moneyball (also referenced by Viktor Mayer-Schonberger and
Kenneth Cukier, authors of Big Data). Billy Beane, the general manager
for the resource-poor Oakland As, understood that trying to solve
problems (such as losing star players and needing to replace them) the
same way that the resource-rich New York Yankees would, was not
feasible. Beane understood that you had to radically redesign the team
using an entirely different set of data points and analytic methods. With
the right data points, from multiple different angles, and a different
mindset, he redefined how baseball teams are designed.

9.  Billy Beane used data and a radically new theory to challenge baseball insiders’
assumptions about how to craft a winning team. At the base of the iceberg are our
mental models or assumptions that drive the way we design or connect the elements
of the system. Jay Forrester, a leading systems thinker, says this of mental models:
“The image of the world around us, which we carry in our head, is just a model.
Nobody in his head imagines all the world, government or country. He has only
selected concepts, and relationships between them, and uses those to represent the
real system.” Mental models are challenged when we test them. Simulations are one
way of testing our assumptions or playing out a scenario. An excellent example of a
team leveraging simulations is Climate Interactive. This group specializes in
environmental issues and has developed multiple simulation tools for policy analysis
and scenario testing. For example, they have created a simulation that examines
drought and displacement scenarios. The simulation encourages users to play out
different scenarios by manipulating key variables such as international assistance,
rainfall and land quality.

10.  Right off the bat I can imagine how principals and school leaders would
be able to use a programming and scheduling simulator to test different
scheduling scenarios for student and school level needs. Well
conducted, rigorous program evaluations will also continue to serve as
an important mechanism for challenging assumptions and theories of
change. Carol Weiss, author of Evaluation, says “evaluation findings
often have significant influence; they provide new concepts and angles
of vision, new ways of making sense of events, new possible directions.
They puncture old myths.”