Why research needs complexity entrepreneurs

By Gabriele Bammer and Jean Boulton.

authors_gabriele-bammer_jean-boulton
1. Gabriele Bammer (biography)
2. Jean Boulton (biography)

What is required to improve the understanding of research teams about the complexity encountered when investigating real life situations? How can they effectively embrace the paradoxical, elusive dance―the irreconcilable, intrinsic tension―between order and disorder, form and formlessness, and certainty and uncertainty? What is involved in research better supporting those intent on, or tasked with, acting skilfully in this complex world? Would a new research role―that of complexity entrepreneur―help?

We have coined the term “complexity entrepreneur” as a shorthand way to describe the attributes required to respond effectively in a world that is complex: ie., systemic, patterned and particular to context, and where newness often emerges in ways that cannot be predicted.

In this i2Insights contribution, we outline the key attributes of a complexity entrepreneur, based on Jean’s work. We then briefly describe the contributions of complexity entrepreneurs to research teams tackling complex problems, combining Gabriele’s and Jean’s work. Our aim is to test the water to see if others would also find benefit in distinguishing this newly-coined role of complexity entrepreneur.

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The essential conditions for, and characteristics of, complexity

By Jean Boulton.

jean-boulton
Jean Boulton (biography)

What are the underpinning necessities or conditions—the essential ingredients—that lead to and engender the qualities or characteristics of the complex world, especially its processual and emergent nature?

Three conditions for complexity: the essential ingredients

A watch or intricate machine is not complex. Nor is a saucer of water. So, when do we regard something as complex? What are the necessary conditions for complexity fully to be realised?

These are:

  • open boundaries
  • diversity
  • reflexive inter-relationships among constituents.

Let’s look at each of these in more detail.

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Data variety and why it matters

By Richard Berry.

richard-berry
Richard Berry (biography)

What are the differing characteristics of data? Why are they important for systems to function effectively? What is requisite variety of data?

There are nine characteristics of data variety which agitate systems. These are volume, velocity, variety, veracity, validity, vulnerability, viscosity, vectors and virtualisation. Together, the ‘9Vs’ constitute a data requisite variety framework and are described below. 

1. Volume

Description: The amounts of available data.

Example: Volume can vary widely from the results of small-scale research to the tsunami of digital material accessible through the internet. The latter can overwhelm both people and organisations.

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How measuring impact gets in the way of real world change

By Toby Lowe

toby-lowe
Toby Lowe (biography)

Why is the idea that we can measure our impact to understand how well we are performing fundamentally flawed? Why is it impossible to “demonstrate your impact” in complex environments?

Although the idea of measuring impact is seductive, almost all useful social change is achieved as part of a complex system. In other words, your work is a small part of a much larger web of entangled and interdependent activity and social forces.

The systems map of the outcome of obesity, shown in the figure below, illustrates this perfectly – it shows all the factors contributing to people being obese (or not), and all the relationships between those factors.

This is the reality of trying to make impact in the world – your actions are part of a web of relationships – most of which are beyond your control, many of which are beyond your influence, quite a few of which will be completely invisible to you.

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Managing complexity with human learning systems

By Toby Lowe

toby-lowe
Toby Lowe (biography)

How can those in public service – be they researchers, policy makers or workers in government agencies, private businesses managers, or voluntary and community organisation leaders – think more effectively about improving people’s lives, when they understand that each person’s life is a unique complex system?

A good starting point is understanding that real outcomes in people’s lives aren’t “delivered” by organisations (or by projects, partnerships or programmes, etc). Outcomes are created by the hundreds of different factors in the unique complex system that is each person’s life.

In other words, an outcome is the product of hundreds of different people, organisations, and factors in the world all coming together in a unique and ever-changing combination in a particular person’s life. Very little of what influences the outcome is under the control or influence of those who undertake public service.

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Can foresight and complexity play together?

By James E. Burke

author_james-burke
James E. Burke (biography)

What is foresight and how does it differ from prediction? What role can complexity play in foresight? Does Cynefin® offer a possible framework to begin integrating foresight and complexity?

In this blog post, I describe how:

  • Foresight identifies clues for the future and integrates them into forecasts
  • Complexity theory offers ways to understand how the future emerges
  • Cynefin® gives us a framework of domains that allows us to better understand trends and forecasts.

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Three complexity principles for convergence research

By Gemma Jiang

author_gemma-jiang
Gemma Jiang (biography)

How can principles adapted from complexity thinking be applied to convergence research? How can such principles help integrate knowledge, methods, and expertise from different disciplines to form novel frameworks that catalyze scientific discovery and innovation?

I present three principles from the complexity paradigm that are highly relevant to convergence research. I then describe three types of transformative containers that I have developed to create enabling conditions for applying complexity principles to convergence.

1. Ecosystem consciousness: An inversion of perspectives

Ecosystem consciousness is necessary because in complex systems the whole (ecosystem) is bigger than the sum of its parts; the wellbeing of the whole and the parts are interdependent and mutually reinforcing.

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Fifteen characteristics of complex social systems

By Hamilton Carvalho

Author - Hamilton Carvalho
Hamilton Carvalho (biography)

What is it about complex social systems that keeps reproducing old problems, as well as adding new ones? How can public policy move away from what I call the Mencken Syndrome (in reference to a quotation from American journalist Henry Mencken) – that is, continually proposing clear and simple solutions to complex social problems – that are also wrong!

With this goal in mind, I have compiled a list of fifteen major characteristics of complex social systems based on the system dynamics and complexity sciences literatures, as well as my own research.

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Accountability and adapting to surprises

By Patricia Hirl Longstaff

Image of Patricia Hirl Longstaff
Patricia Hirl Longstaff (biography)

We have all been there: something bad happens and somebody (maybe an innocent somebody) has their career ruined in order to prove that the problem has been fixed. When is blame appropriate? When is the blame game not only the wrong response, but damaging for long-term decision making?

In a complex and adapting world, errors and failure are not avoidable. The challenges decision-makers and organizations face are sometimes predictable but sometimes brand new. Adapting to surprises requires more flexibility, fewer unbreakable rules, more improvisation and deductive tinkering, and a lot more information about what’s going right and going wrong. But getting there is not easy because this challenges some very closely held assumptions about how the world works and our desire to control things.

Let’s not kid ourselves. Sometimes people do really dumb things that they should be blamed for. What we need is to be more discriminating about when finding blame and accountability is appropriate.

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Foundations of a translational health sciences doctoral program

By Gaetano R. Lotrecchiano and Paige L. McDonald

authors_gaetano-lotrecchiano_paige-mcdonald
1. Gaetano R. Lotrecchiano (biography)
2. Paige L. McDonald (biography)

How can doctoral studies be developed to include innovation in practice and research, as well as systems and complexity thinking, along with transdisciplinarity? This blog post is based on our work introducing a PhD in Translational Health Sciences at George Washington University in the USA.

Innovation in Practice and Research

We suggest that innovation in practice and research is achieved by the integration of knowledge in three key foundational disciplines:

  • translational research
  • collaboration sciences
  • implementation science (Lotrecchiano et al., 2016).

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Managing deep uncertainty: Exploratory modeling, adaptive plans and joint sense making

By Jan Kwakkel

jan-kwakkel
Jan Kwakkel (biography)

How can decision making on complex systems come to grips with irreducible, or deep, uncertainty? Such uncertainty has three sources:

  1. Intrinsic limits to predictability in complex systems.
  2. A variety of stakeholders with different perspectives on what the system is and what problem needs to be solved.
  3. Complex systems are generally subject to dynamic change, and can never be completely understood.

Deep uncertainty means that the various parties to a decision do not know or cannot agree on how the system works, how likely various possible future states of the world are, and how important the various outcomes of interest are.

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Scaling up amidst complexity

By Ann Larson

ann-larson
Ann Larson (biography)

How can new or under-utilized healthcare practices be expanded and institutionalized to achieve audacious and diverse global health outcomes, ranging from eliminating polio to reversing the rise in non-communicable diseases? How can complex adaptive systems with diverse components and actors interacting in multiple ways with each other and the external environment best be dealt with? What makes for an effective scale-up effort?

Four in-depth case studies of scale-up efforts were used to explore if there were different pathways to positively change a complex adaptive system.

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