CHAPTER 1
Complexity Thinking

Dr. Gerry Gingrich, instructor at the Information Resources Management College, National Defense University, states: “Military thinkers, politicians, scientists, and corporate executives are all looking for ways to understand the dynamics of global change and to prepare for the 21st century. Many are looking to the new science of complexity for answers. The science of complexity, however, does not yield answers, at least not in the sense that we have typically sought to describe our world and predict its events since the beginning of the Scientific Revolution. What it does yield is a new way of thinking about the world.”¹

Complexity is one of those words that is difficult to define. Some say complexity is the opposite of simplicity; others say complicated is the opposite of simple while complex is the opposite of independent. A complex structure is said to use interwoven components that introduce mutual dependencies and produce more than the sum of their parts. In today’s business systems, this is the difference between myriad connecting “stovepipes” and an effective set of “integrated” solutions.²

A complex system can also be described as one in which many different components interact in multiple ways.³ In the context of a design that is difficult to understand or implement, complexity is the quality of being intricate and compounded.⁴ When project managers characterize a project as complex, they usually mean the project is “… challenging to manage because of size, complicated interactions, or uncertainties. Often, anxiety goes hand in hand with complexity.”⁵

Complex systems and complexity theory have captured the attention of scientists in the fields of anthropology, physics, biology, ecology, economics, political science, psychology, native studies, sociology, finance, and management. Since business organizations as well as project teams are complex systems, the science of complexity theory offers a way to understand and work with the complex nature of organizations and projects. Because complex systems are largely unpredictable, thinking about business systems as complex requires a paradigm shift from long-established business models based on control theory, which is essentially an attempt to manipulate the inputs to a system to obtain a desired effect on the output of the system.⁶

Complexity scientists are careful to differentiate between complicated and complex. Complicated is considered to have input and output flows and straightforward cause and effect (as in machines), where the pieces can be well understood in isolation and the whole can be reassembled from the parts; one problem can bring the system down, since complicated systems do not adapt.⁷ Complex, in contrast, is adaptive (as in ecosystems), with cycles, interrelationships, interdependencies, nested systems within systems, and multiple feedback loops. Examples of complex systems include weather systems, the Internet, the U.S. power grid, highways, supply chains, information transfer within organizations, business systems, and business organizations themselves. According to Julio Ottino, professor at the R.R. McCormick School of Engineering and Applied Sciences at Northwestern University, “The hallmarks of these complex systems are adaptation, self-organization and emergence—no one designed the web or metabolic processes within a cell.”⁸

COMPLEX SYSTEMS AND COMPLEXITY THEORY

Scientists originally thought the world to be linear, explained by simple cause-and-effect relationships. They theorized that if we could break down natural systems into their component parts, we could not only understand them but also learn how to predict and control them. Gradually, however, complexity theory emerged.

Complexity theory had its beginning in the 1980s at a think tank known as the Santa Fe Institute. Researchers ranging from graduate students to Nobel laureates formulated the theory that the application of ideas like complexity, adaptation, and turmoil at the edge of chaos can begin to explain “… the spontaneous, self-organizing dynamics of the world in a way that no one ever has before—with potential for immense impact on the conduct of economics, business, and even politics. They believe they are forging the first rigorous alternative to the kind of linear, reductionist thinking that has dominated science since the time of Newton—and that has now gone about as far as it can go in addressing the problems of the modern world.”⁹

Complexity theory is based on relationships, emergence, patterns, and iterations. It maintains that the universe is full of systems (e.g., weather systems, immune systems, social systems) that are complex and are constantly adapting to their environment; hence the term complex adaptive systems¹⁰ Creativity manifests itself in spontaneous emergence, which is at the center of complexity thinking. Emergence is the result of the intricate interplay of dynamics, forces, and energies. Creativity emerges in systems that are constantly evolving, reorganizing, or dissolving into chaos. The genius of complexity thinking is that it nourishes and masters creativity, never trying to lock it into systems, subsystems, or parts.¹¹

Complexity theory states that systems exist on a spectrum ranging from equilibrium to chaos. Equilibrium results in paralysis and death; chaos results in an inability to function. The most productive state to be in is at the edge of chaos, where maximum diversity and creativity lead to new possibilities¹² (Figure 1-1).

FIGURE 1-1. The Edge of Chaos, the Most Productive State

COMPLEX ADAPTIVE SYSTEMS

Complex adaptive systems are a specific type of complex system. These systems are complex in that they are diverse and comprise multiple interconnected elements; they are adaptive in that they have the capacity to change and learn from experience. The term “complex adaptive system” was coined at the Santa Fe Institute. In his essay, A Brief Description of Complex Adaptive Systems and Complexity Theory,¹³ Peter Fryer describes the most important properties of complex adaptive systems:

• Emergence. Rather than being planned or controlled, the agents in the system interact in apparently random ways. From all these interactions, patterns emerge that inform the behavior of the agents within the system and the behavior of the system itself.

• Co-evolution. All systems exist within their own environment and they are also part of that environment. Therefore, as their environment changes, they need to change to ensure best fit.

• Sub-optimal. A complex adaptive system does not have to be perfect to thrive within its environment. It only has to be slightly better than its competitors; any energy used on being better than that is wasted energy.

• Requisite variety. The greater the variety within the system, the stronger it is. In fact, ambiguity and paradox abound in complex adaptive systems, which use contradictions to create new possibilities to co-evolve with their environment.

• Connectivity. The ways in which the agents in a system connect and relate to one another are critical to the survival of the system, because it is from these connections that the patterns are formed and the feedback is disseminated.

• Simple rules. Complex adaptive systems are not complicated. The emerging patterns may have a rich variety, but the rules governing the functioning of the system are quite simple.

• Iteration. Small changes in the initial conditions of the system can have significant effects after they have passed through the emergence-feedback loop a few times (often referred to as the butterfly effect).

• Self-organizing. There is no hierarchy of command and control in a complex adaptive system. Rather than planning or managing, there is a constant reorganizing to find the best fit with the environment.

• Edge of chaos. Complexity theory is not the same as chaos theory, which derives from mathematics. But chaos does have a place in complexity theory in that systems exist on a spectrum ranging from equilibrium to chaos.

• Nested systems. Most systems are nested within other systems, and many systems are made up of smaller systems.

BUSINESSES AND PROJECT TEAMS AS COMPLEX ADAPTIVE SYSTEMS

Complex adaptive systems are all around us: ant colonies, weather systems, the immune system, the brain, the stock market, business systems, and any group of people who are working toward similar goals, such as political parties, communities, businesses, and yes, project teams. The principles of emergence and self-organization are relevant in all these systems. Complex adaptive systems are a model for thinking about the world around us—but not a model for predicting what will happen.

Businesses are complex adaptive systems nested within a larger complex adaptive system, the global economy. Just as complex adaptive systems in nature fluctuate among the states of equilibrium, edge of chaos, and even chaos depending on their environment, so will a company fluctuate among these states. A business may at times operate in chaos, particularly when old ways of doing things need to be abandoned and new ways need to be found to explore and experiment with a variety of alternatives in an innovative manner. This fluctuation represents the capacity to adapt to changing environments, which is essential to our very survival. As managers we need to allow for and encourage diversity of thought and exploration if we are to achieve creativity and adaptability, even though operating on the edge of chaos may be quite unsettling.¹⁴

NOTES

1. Gerry Gingrich, “Simplified Complexity: Thinking in the White Spaces,” May 1998. Online at http://www.stormingmedia.us/56/5624/A562493.html (accessed January 2008).

2. Michael R. Lissack and Johan Roos, The Next Common Sense: The e-Manager’s Guide to Mastering Complexity. (London: Nicholas Brealey Publishing, 2002).

3. D. Rind, “Complexity and Climate,” Science Magazine, vol. 284, no. 5411 (1999), 105-107.

4. Luay Alawneh et al., “A Unified Approach for Verification and Validation of Systems and Software Engineering Models,” 13th Annual IEEE International Symposium and Workshop on Engineering of Computer-Based Systems (2006), 409-418.

5. B. Michael Aucoin, Right-Brain Project Management: A Complementary Approach (Vienna, VA: Management Concepts, 2007), 132.

6. Roger Lewin and Birute Regine, “On the Edge in the World of Business,” afterword to Complexity: Life at the Edge of Chaos by Roger Lewin (Chicago: University of Chicago Press, 1992), 198.

7. J. M. Ottino, “Engineering Complex Systems,” Nature 427 (2004). Online at www.nature.com/nature (accessed January 2008).

8. Ibid.

9. M. Mitchell Waldrop, The Emerging Science at the Edge of Order and Chaos (New York: Simon & Schuster, 1992), 12-13.

10. Peter Fryer, “A Brief Description of Complex Adaptive Systems and Complexity Theory.” Online at http://ryanlanham.wordpress.com/2007/09/01/trojanmicecom-what-are-complex-adaptive-systems (accessed January 2008).

11. Vladimir Dimitroy, “Complexity, Chaos and Creativity: A Journey Beyond System Thinking.” Online at http://www.zulenet.com/VladimirDimitrov/pages/complexthink.html (accessed January 2008).

12. Peter Fryer, “A Brief Description of Complex Adaptive Systems and Complexity Theory.” Online at http://www.trojanmice.com/articles/complexadaptivesystems.htm (accessed January 2008).

13. Ibid.

14. Roger Lewin and Birute Regine, On the Edge in the World of Business, afterword to Complexity: Life at the Edge of Chaos by Roger Lewin (Chicago: University of Chicago Press, 1992), 201.