How Complexity Science can Support Strategic Foresight

In honor of World Future Day, which is celebrated annually worldwide on March 1st, we are sharing our favorite foresight terms all month long to raise awareness of Strategic Foresight. Today’s term is “Complex Systems.”

“I think the next century will be the century of complexity.”

-Stephen Hawking, San Jose Mercury News, January 23, 2000

The challenge of planning when the future is unpredictable

All good professional futurists will tell you that the future cannot be predicted, an idea that is increasingly mainstream. Yet despite recognizing the patent truth of this fact (evidenced  by surprises in markets, electoral politics and culture), organizational leaders rely on planning tools that assume that the future will be like the past, and thus can be predicted. This is at least in part because of the paradox that planning in an unpredictable world suggests it is genuinely difficult to visualize how to plan for what cannot be predicted. How would you start?

We propose beginning with a precise understanding of complex systems, which is our strategic foresight term for this week. This term comes from complexity science, a framework that has provided a theoretical basis to better understand why the world is unpredictable. This framework can help decision-makers model how events in a complex environment could unfold, rather than seeking to reduce their complexity (which cannot be done).

The definition of a complex system

Although the term “complex” is used in an everyday sense to mean anything that is intricate or difficult, the word has a specific meaning in the study of systems: “complexity” is an aspect of some systems, which are aptly called “complex systems.” Examples of complex systems include insect colonies, the human immune system and the global stock market. Despite their differences, all of these share several qualities:

  • complex collective behavior: many parts or components act according to simple rules that, in combination, generate difficult-to-predict patterns in the system as a whole.
  • information processing: the use of information from interna and external environments.
  • adaptive behavior: complex systems learn and evolve new behaviors that amplify their chances of success.

(list adapted from Dr. Melanie Mitchell’s, Complexity: A Guided Tour)

From the point of view of complexity science, complex systems are distinct from complicated systems. Complicated systems can have many components and can be challenging to understand. Nevertheless, a complicated system (such as the engine of an airplane, for example) can be reduced to its component parts. Complex systems cannot be reduced in the same way because their components may change in response to their immediate environment; they are dynamic, rather than static.

The characteristics of complex systems make their behavior in the future difficult to predict or forecast, and the tools required to understand the potential futures of a complex environment are different from those required to understand a complicated system.

How to optimize planning in a complex system

Planning that confronts the reality that the broader business environment is a complex system can feel especially challenging. It differs from planning in the strategic planning paradigm of the mid-20th century, in which it was expected that the future could be predicted by extrapolating from the past. It may use the tools of strategic foresight, which were designed for addressing uncertainty and complexity.

Planning in complexity requires wrestling with unpredictability and managing stakeholder and market discomfort with uncertainty.  

Indeed, the goals of planning are different in complex systems, as scientists at Sandia National Laboratories have suggested: In today’s complex, interconnected, and uncertain world, the best policy decisions are those that result in expedient and advantageous solutions in the near-term while avoiding undesirable outcomes in the long-term. To inform such decisions, the goal of the analyst is not to find ‘optimal’ answers to policy questions, but to reduce uncertainty and risk in their effects.

Futurists play a role in this transformation by partnering with leaders and planners to introduce mindsets and implement planning tools designed for complex systems.

Take action to begin planning for a complex environment:

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