Embracing complexity: strategic perspectives for an age of turbulence: A review by Danai Charalampidi

Chapter 1: Introduction

This book discusses two contrasting world views: the mechanical worldview and the complexity worldview. Through the former, the world operates like a machine which implies that the future is a predetermined path towards which, there is no adaptation, variety or surprise.

On the contrary, the complexity worldview suggests that everything is interconnected, which makes the world full of forms and patterns that are historically and contextually influenced. Rather than the future being predictable, things are in the process of “becoming”, a concept that has its roots in philosophy and mathematical modelling.

Despite of the mechanical worldview often seeming attractive, as it provides a sense of order, purpose and control, the authors’ primary aim is to challenge it, as they believe it has political and scientific implications on how humans operate collectively and envision the future.

Complexity thinking, as a means to explore the world, is being analysed through a wide range of perspectives, both via theoretical concepts and practical examples through the following chapters.

Chapter 2 – The nature of a complex world.

 Due to the fact that complexity thinking was primarily developed by mathematical models, which in practice can be challenging to understand, in this chapter the authors introduce some of its key concepts and terminology through an analogy of the life cycle of forests based on ecologist’s Buzz Holling’s observations.

Even though the social world is not as “tidy” as the forests’ ecosystems, the latter can bring to light the value of certain of its patterns. For example, in the case of a stable environment, as the system grows harmoniously, its elements self-organize and result in non-predictable relationships and forms.

On the contrary, when a forest is not as stable and during its development experiences greater fluctuations, it is likely to be in a “tipping point”, which could either result in its collapse, and inevitable rebirth of its cycle, or it could self-regulate and create unexpected patterns.

The role of the “messiness, variation, diversity and fluctuation” as embraced though the forests’ ecosystems can inform how humans operate to face change and adapt with “resilience” to the unknowns of the future.

Chapter 3 – Unpacking Complexity.

 The core of complexity thinking can be analysed as an ontological query, a means to explore the world. In this chapter, the authors provide some key insights on its theoretical origination through Ilya Prigogine’s work. His interest was triggered by the apparent disconnect between physics, with particular interest in Newtonian mechanics, and biology, with focus on thermodynamics.

The primary issue that initiated his research was that both principles’ findings, despite being contradictory, were applied to almost every situation in the human and natural world. He deemed that to be unrealistic due to the fact that both physics and biology experimented on “closed systems” (whose elements cannot interact with anything else outside themselves). The former considered interactions to be predictable, reversible and casual, whilst the latter considered that they decay, disorganise and move towards thermodynamic equilibrium.

Despite both scientific explanations touching on “change”, which complexity theory is greatly concerned with, the world is an “open system” through which information, energy and matter are being exchanged with its environment and can result in emergent structures. That, in its core, is the basis of “evolutionary” change which characterises the complex world.

Its nature is defined as being systemic, multi-scalar, path-dependent, being adaptable to change, is able to self-organise and because of that, have multiple futures.

Chapter 4 – Have we thought like this before?

In order to assess the “validity” of complexity thinking as more than a simple “theory”, or purely a science, but a hybrid that embraces both, this chapter discusses some influences of the past that assisted the formation of the notion.

Initially, the authors reference some of the pre-Socratic theorists from the 6th century BC onwards, outlining that even from that time, the ideas of “change, interconnection, co-creation”, and importance of “particularity of events” were key to the understanding of the world from various perspectives.

Following that, they discuss how the concept of change starting from Plato who explored nature as the design of “the Divine Craftsman”, that strives towards an “end” with ultimate purpose the perfection of its elements, to referencing the scientific experiments of Newton and thermodynamics as previously mentioned.

Even though philosophy and science at the time were considered to disconnect, they both relied -to some degree- to a metaphysical/ spiritual explanation when faced with the uncertainty of the future in a real-life context.

Darwin, conversely, introduced the idea of evolution through which he highlighted the importance of variation and selection, the role of the past in shaping the future, and the inevitability of the unexpected. Those, in combination with Prigogine’s findings on “fluctuation” and “tipping points”, which implied that the world is under “perpetual construction”, resulted in the emergence of complexity thinking.

Chapter 5 – The complexity of complexity theories.

Complexity theories have been primarily developed by mathematical models, which present a “problem” in abstract form through mathematical equations. There is a plethora of types of models which explore different issues and based on the desired outcome or prediction the modeller has to make assumptions and simplifications. This, of course, inevitably has implications when the model is applied in a real-life scenario where there is so much variety, change and the future cannot be determined completely.

This chapter analyses some of the key categories of models and their specific consequences when applied in the complex world. One of the core dilemmas presented through it is whether it is preferable to work in a narrow context rich in detail or on a wider one with simplified or even averaged information.

To approach complexity theory as closely as physically possible the most appropriate type of complex model is the “evolutionary” one. Typically, the two core assumptions that modellers of those make are that the investigated system has a boundary and that its elements can be classified into “types”. In practice, in order to achieve multiple “futures”, the model in addition to its core structure will include “random noise”, which gives it the option to choose and adapt to the unexpected, or even take an entirely new form.

Chapter 6 – Complexity and the social world.

From this chapter onwards, the authors apply the complexity theory to real-life scenarios of the world such as organisations and societies. In this chapter they discuss the differences between human systems and the modelled ones. Even though the latter ones can give us insight on how new qualities emerge and can simulate interactions that are “non-linear” and “reflexive”, they can never provide a single “right” answer.

Human beings unlike molecules, “can reflect on, analyse, imagine, create intentions towards and consciously and unconsciously affect the social and natural systems of which they are a part of.” In living systems the behaviour at a given time is determined by memory and by the anticipation of the future. Despite their differences, both human and non-human systems self-organise which is a key concept of complexity theory.

On the second part of the chapter the authors analyse how the complex world can be researched thoroughly. Initially, they present the core issues around the traditional research methods whose typical processes link theory to data, but they are most usually quantitative rather than qualitive.

On the contrary, a “complexity informed research process”, embraces the unexpected which emerges during the investigation, reflects change over time, represents various views and does not rely on a hypothesis made at the start of the inquiry. These can be achieved by using narrative or case studies. Alongside those, to understand the future(s) of the complex world, humans need to embrace empiricism and evidence based judgement.

Chapter 7 – Complexity and Management.

This chapter argues that complexity thinking can be applied to resolve managerial issues which arise when perceiving the world through the “mechanical perspective”. If organisations deal with their projects and teams as if they are predictable, uniform and controllable, then they are limited to purely understanding what is happening, rather than deciding how to move forward and stop repeating inevitable mistakes.

This can be achieved by adapting the existing methods that are being used, embracing the unpredictability of the future and accepting that history is of pivotal significance. Both project and management teams need to be adept at looking forwards and backwards. They need to pay attention to the details and particularities of the context -wide and narrow-, look for synergies and factors that may affect progress even if these are outside the focus of the project. They must not assume that “one size fits all”.

Complexity thinking highlights the problematic areas of leadership and its ways of interacting with others. There needs to be additional focus on participation, dialogue and creation of shared intentions. Judgement, as within the context of a complex model, is essential, in order to balance clarity, adaptability and diversity successfully.