The challenges of a highly interconnected world need systemic answers

Keks Ackerman
Sep 14, 2018 · 11 min read
Leonardo da Vinci, Town plan of Imola

To be effective, the kind of innovations we need to develop for some of the most urgent contemporary challenges — among them environmental destruction, the wealth gap and the loneliness crisis — need a wider perspective which takes complexity into account. We need to look at problems not in isolation, but in their context: the broader system they are embedded in. In a highly interconnected world, the relationships between cause and effect change. Instead of being linear and predictable, phenomena are non-linear and thus difficult to predict. If we approach complex, systemic questions with a linear logic, we will at best create mechanisms that are ineffective or, at worst, contribute to the collapse of the larger system.

In this post, I’ll be looking at some basic principles of systems. By now there exists a huge literature in various disciplines about systems, most of which I’ll ignore. Instead I want to present some fundamental concepts that are essential for understanding how we can approach and facilitate effective social, economic, ecological and political change. This knowledge should enable us to discern if an innovation has the potential to answer a given challenge or if it falls short of it because the frame of reference is too narrow and linear. It should also inform us how to approach the design of our own business, product or service.

Taking the AQAL (introduced in the third blogpost of this series) as a map of orientation, this post focuses primarily on dynamics in the lower right quadrant of collective and exterior phenomena. It also touches upon the upper left quadrant — our individual attitudes and filtering mechanisms — as these need to adapt and expand if we want to come up with ideas, products and services suitable for changing systems.

Graphic by Keks Ackerman, licensed under CC BY-NC 2.0, based on Ken Wilber’s AQAL

You don’t meet a system on the street
Before exploring different aspects of the systems perspective, we need to add a word of caution: You can’t meet systems “on the street” — as tangible, fixed objects in the world. Instead, a systemic view is always a particular perspective on reality. It is a way of looking at things not in isolation, but in a wider context. As ultimately everything in life is connected to everything else and we can slice reality into all kinds of segments, we need to make conscious decisions of what parts of „the whole“ we want to include in our systemic analysis. The elements our system consists of depends on the questions we are trying to answer. If, for instance, we are looking at an innovative food production process and wanted to evaluate its impact on African farmers, we might need to include trade regulations and financial institutions such as the stock exchange in our systems analysis. If we were instead interested in its effect on the environment, we might include climate-engineering technologies in our assessment.

A system is a set of related components that work together in a particular environment to perform whatever functions are required to achieve a systems objective.

One definition of a system by Donella Meadows

Attributes of Systems
What characterises systems and what do innovators intervening in systems need to take into account? Systems come with a few important attributes which govern their behaviour. Here are some of the characteristics system thinkers focus on: First of all, there are interconnections: Everything is connected to each other. These parts form certain patterns which can be observed. They are characterised by emergence — new forms appear when parts of the system come together, often in self-organised ways. The elements of a system are creating constant feedback loops among each other. System theorists distinguish between reinforcing feedback loops (which lead to instability and uncontrolled growth) and balancing feedback loops, which are stable and self-correcting. Finally, not everything in a system is random; there are causal relationships between some of the elements, which can be identified.

Simple, Complicated, Complex and Chaotic
Elements of a system interact with each other in various degrees of intensity and complexity, creating different environments for effecting change. Systems thinkers distinguish between four settings, all with distinct relationships between cause and effect. These are simple,complicated, complex and chaotic. Here is an easy shorthand for these categories: When baking a cake according to a recipe, we are confronted with a simple task. Putting a man on the moon is complicated. Raising a child is complex, and September 11 was a chaotic event.

Now let’s look at these four settings in more detail, focussing on how to navigate, innovate and make decisions in each one of them.

Simple
Simple situations occur if we can discern clear and stable cause-effect relationships. In these settings, leaders or innovators sense and assess the facts of a problem, categorise it and respond in a pre-set way. In these settings, command and control-style management works well, directives can be straightforward, decisions can be delegated and many functions can be automated. „Simple“ settings are those with “known knowns“. When making a cake, I follow a simple, linear description and should get a predictable result.

Complicated
Complicated situations also have clear cause-and-effect relationships. But because many factors are at play, not everybody sees and understands them. Thus complicated problems call for experts — people with highly specialised knowledge to inform others or innovate new processes. Here leaders sense and access the facts, analyse them and respond. „Complicated“ settings are those with „unknown knowns“. When putting a man on the moon, lots of experts come to work together, adding their parts to make the whole.

Complex
In complex situations, there is no single and clear right answer. When situations are highly interconnected it’s impossible to identify simple cause-and effect relationships. Situations are fluid, unpredictable and constantly changing. Instead of following a recipe or listening to specialists in one topic area, leaders and innovators have to watch the system move, identify patterns and detect new answers to emerge. “Unknown unknowns” characterize “complex” problems. When raising a child, parents can shape the direction of development by carefully sending impulses and being attentive to the child’s potential, but no pedagogic intervention has a predictable outcome and the whole — the child — is much more than the sum of the parts which went into the education.

Chaotic
Finally, Chaotic situations are the domain of occurrences that could not have been predicted before. They are the realms of the „unknowables“. Leaders trying to get a grip on chaos can’t wait for a solution to emerge, but need to act decisively, sense the outcome and then respond. In the case of the terrorist attacks on the World Trade Center in September 2001, New York’s mayor Rudy Giuliani acted in a calm yet forceful way in a moving speech which reassured the city’s residents and prevented wider social chaos.

Mixing it up
In our contemporary world, many people confuse complicated with complex situations, often mistaking the latter for the former. They assume that a certain level of predictability and order still exists in many policy situations and that linear cause-effect relationships are at play. But once a phenomenon is part of a larger, interconnected system, the mechanical laws of management and Newtonian science don’t apply any more. Instead we are confronted with non-linear, often exponential developments. As most of us can only hold a few moving variables in our minds, complex situations are difficult to grasp intellectually. Instead we need to develop new complementary methods to develop adequate answers to complex challenges. I’ll come back to this towards the end of the article.

What happens if you optimise a subsystem
In our inability to address complex problems in an adequate, i.e. systemic way, we can recognise patterns. One prominent pattern is the tendency to optimise subsystems, instead of the whole system.

Every system consists of various subsystems that can most likely themselves be divided into new subsystems. Lacking a whole system perspective, most policy makers and innovators tend to focus their attention on subsystems instead. This tendency to optimize parts not only results in identifying the wrong problem, it often leads to a deterioration of the whole system as it has a destabilising effect.

For example, let’s say a policy maker wants to improve some of the daunting social problems relating to families. Very likely a systems approach is needed. But the fragmented administrative structures of most countries are standing in the way of a systemic policy approach. In Germany, for example, the state doesn’t deal with family policy directly, except for coordinating funding among various ministries on the top level. Family affairs are subject to a whole range of different ministries (education, family, finance, welfare, health, security etc.), as well as on different geographical levels (state, district, municipality etc.). Very likely isolated change in one of these areas is going to negatively affect other areas, leading to counterproductive results.

One small example: Education is one of the most important areas for national policy making, as well as family welfare. In Germany, teachers are paid by the federal government, but municipalities (Gemeinden) have to pay for the upkeep of school buildings. If a municipality with a declining school population wants to close a school in order to save money, another administrative level in between the federal level and the municipality, the district (Landkreis), has to pay for the school bus transporting the pupils from the closed school to another one in a neighbouring district. Now, these transport costs might be higher than the costs for the upkeep of the school building. But as the costs show up in different budgets, a probably inferior solution (closing the school) gets implemented, as nobody views the decision holistically. The subsystem is optimized, while the whole system is weakened. A whole-system perspective in contrast would identify the overarching goals of schools and analyse tensions and contradictions between the different administrative units, developing answers across them.

This phenomenon of focusing on subsystems often leads to completely irrational outcomes, such as refugees being hosted in expensive hostels, or unstable families being overwhelmed by a battery of social workers who attempt to address small pieces of the puzzle without a comprehensive analysis of a family’s needs. The latter case is described by Hilary Cottam, a British social designer, in her recent book “Radical Help” (2018). Working with “troubled families” in Swindon who were suffering from financial, social and psychological deprivation, Cottam observed how more than 70 different services run out of 24 different departments intervened for the “well-being” of these families. In a normal week, a family might have various social workers, youth workers, home tutors, housing officers, police officers and others intervene in their family life, mostly answering standardized questions and filling out forms. None of these actions were part of a general plan with an end goal and none of these interventions focussed on the underlying issues. Managing all these social workers with their different requirements and expectations turned out to be a full-time job for heads of households.

A perspective that identifies and maps the different interventions and their repercussions within the wider system would be able to create not only significant efficiencies, but much better qualitative outcomes. (In the Swindon case, despite staggering costs, not one of the families “aided” by the current system managed to improve). Cottams approach seems deceptively simple: she and her team set up base on one of the estates where “troubled families” lived and began a dialogue, asking the families what changes they themselves would like to see in their lives. Suddenly new answers emerged and Cottams team helped to facilitate the next steps, strengthening the relationships between family members, connecting them to new work opportunities, and introducing them to healthier lifestyles. There were no spectacular transformations, but sustained and positive progress at a fraction of the cost of existing services.

Holding complexity and seeing emergence
In complex situations — and innovators seeking to address social and environmental problems are most likely confronted with complex rather than simple of complicated settings — we have two options. We can try to reduce complexity from the start in order to find an easy solution. This is unlikely to work, as complexity by its very nature resists easy answers. Alternately, we can accept that solving the problem involves recognising its irreducible complexity, and search for patterns and movements within the system that present suitable leverage points for interventions. This latter approach is more likely to generate outcomes that successfully address the problem.

This approach has important implications for product development. Early on in the design process, innovators need to come up with complex hypotheses for complex problems rather than succumbing to the temptation of simplifying them to generate solutions more easily.

Many startups initially aim to have a large impact, but during the product development process they are often daunted by the real world complexity they are facing. Instead of acknowledging this complexity, they narrow their focus to solving the easy parts of the larger problem and build solutions for those. This often results in the above mentioned optimization of subsystems. The larger vision is lost or only referred to rhetorically. Product designer Mike LaVigne, who describes this common dilemma, advises innovators to maintain the complexity of problems throughout the development process to find better solutions rather than simplifying problems to make solutions easier to find.

Innovators comfortable with dealing with staggering complexity tend to rely on more then their cognitive capacities to understand systems. They speak of „seeing“ and „sensing“ patterns and intuiting possible answers. „You suddenly know what the next step could be“ they say or „I see a movement in the system which points to a leverage point“. Tuning in with the system, they might notice patterns and movements within them, which were not visible before. Often this knowledge is not analytical, but internally felt and sensed. This is what Ken Wilber has called “thinking, feeling, sensing”, and is one of the capacities associated with a „yellow“ perspective in Spiral Dynamics.

It is a quality hard to pin down or learn how to do systematically. Interestingly though, it’s a process which seems to be supported by the use of psychedelics. In his new book, How to Change your Mind, US journalist Michael Pollan describes how creative people, such as engineers and artists, say that LSD or psilocybin has freed them from existing filters and showed them new patterns. The chemical effects of hallucinogens break down boundaries between categories, allowing an appreciation of new combinations of parts and whole systems.

However, taking LSD isn’t the only way to do this. I will be exploring the topic of how to practically approach complexity throughout the innovation process in a future post.

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Suggestions for further reading:

Hilary Cottam, 2018. Radical Help, How we can remake the relationships between us and revolutionise the welfare state. Little, Brown: London

David Snowden, Mary Boone. A Leaders Framework for Decision Making, Harvard Business Review, Nov 2007

Michael Pollan, 2018. How to Change your Mind. What the New Science of Psychedelics Teaches Us About Consciousness, Dying, Addiction, Depression, and Transcendence, Penguin Press: New York

Mike LaVigne, On the road in Pakistan. Creating a new healthcare service, medium.com, August 2018

Future Sensor

A vision for a systemically healthy future which we as innovators, entrepreneurs and policy makers can turn into reality.

Keks Ackerman

Written by

Keks Ackerman is a metamodern writer, and entrepreneur, building a systemically healthy society and economy.

Future Sensor

A vision for a systemically healthy future which we as innovators, entrepreneurs and policy makers can turn into reality.

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