More Recent Trends in Understanding Organization Change: Complex Adaptive Systems and Appreciative Inquiry

Seven years ago, I took a short detour from my career as a violinist and started work on a Master’s degree in Organization Development, which I undertook with hopes of understanding and eventually helping transform the difficult dynamics of orchestra organizations. My own orchestra was going through a particularly rough time, so I had a very personal motivation. The ideas and frameworks I studied were intellectually stimulating, appealed to my idealism and allowed me to take a somewhat more objective view of the issues my orchestra and others were having.
I remained in the program for nearly two years before returning to the violin full-time; it was during that period that Paul Judy asked me to write a series of articles on organization change for the web version of the Symphony Orchestra Institute’s journal Harmony. Those articles describe various approaches to understanding and implementing organization change.
In general, organizational theories have been slow to catch on. Ideas that have generated successful changes (documented with high-profile case studies) have become fashionable for a while; some have had a bright moment and fizzled out, still others have evolved quietly for years before coming into their own. Human organizations are so complicated that no single approach is adequate to understand them; new concepts tend to layer onto, rather than replace, older ones. Many of the ideas included in the 2001- 2002 Harmony series were between fifteen and fifty years old, and were still considered cutting-edge because relatively few organizations were actively trying to put them into practice. In this sequel to those earlier articles, I will be describing two theoretical frameworks: Complex Adaptive Systems and Appreciative Inquiry. Both are relatively new by the standards of the field but have attracted much wider attention during the past ten years.
COMPLEX ADAPTIVE SYSTEMS
From the beginning, organizational theorists looked to the natural sciences for principles that could explain the dynamics of organizations. Biologist Ludwig von Bertanlanffy’s seminal writing on “universal principles applying to systems in general” was the most important influence on the development of Open Systems theory. According to this framework, organizations are considered “open systems” : they take in information and resources from the environment, process them, and in turn their outputs impact that environment, under the same general principles as an individual organism. In the 1990’s, some theorists began refining this idea further, borrowing the concepts and language of a new interdisciplinary field called complexity science.
A complexity theorist would describe an orchestra organization, a flock of birds, or the stock market as complex adaptive systems. A CAS is defined as an entity made up of multiple individuals which continually adapts to its environment and self-organizes in orderly but unpredictable ways. Computer scientists have been quite successful modeling examples of complex adaptive systems. For instance, in a popular computer simulation called Boids, a group of randomly moving virtual birds create beautiful orderly flocking patterns given only a set of three simple steering rules. ( Link: http://www.red3d.com/cwr/boids/) There is no “grand plan”; the pattern self-organizes out of the balance between the Boids’ individual freedom and the minimal specifications they are given. A slight change in one rule would change the pattern completely, perhaps even causing collisions or the disintegration of the group.
Complex adaptive systems share the following principles:

• 1. The characteristics of a CAS as a whole emerge from the actions of individual agents, which are essentially unpredictable
• 2. A CAS tends to organize itself, based on a set of initial conditions, into a stable state called an attractor state.
• 3. Anything which significantly weakens the attractor (or strengthens a different one) frees the system to move to a different state.
• 4. The area of freedom between attractors is defined as “the edge of chaos”, but it is also the point where system learning takes place.
• 5. There are multiple potential states within each system, and any of them can become dominant under the right conditions. Even a small change can flip the system out of equilibrium.
• 6. A CAS exists as a subsystem in a larger CAS: its environment. This means it is not only affected by conditions in the environment, but also is an agent contributing to the emergence of those conditions.

Though a complexity scientist would say that these principles apply to human groups and could be mathematically modelled, most people interested in organizations are likely to treat them as a metaphor. Either way, there are a number of implications for human systems, including:

• 1. Change is an unavoidable feature of all living systems; the challenge is to find ways to embrace and flow with it.
• 2. Top-down leadership is illusory, since the true organization emerges from patterns throughout the system.
• 3. Leadership is holographic: every individual has responsibility for the state of the whole.
• 4. Stable “attractor states” always have a powerful pull; if you want to move to a new one, it needs to be equally powerful.
• 5. In order to move to a different stable state, it is necessary to travel through the edge of chaos.
• 6. The precise characteristics of any future state cannot be predicted or controlled, only shaped to some degree by setting appropriate contexts (analogous to the Boids’ three simple rules).
• 7. It is unrealistic to think of your organization as separate from, or even in competition with, its environment — all are part of one pattern. This reshapes the boundaries between producer and consumer, organization culture and community.

The complexity science metaphor has resonated with people frustrated by the high failure rate of planned organizational change initiatives.
After so many years of defending ourselves against life and searching for better controls, we sit exhausted in the unyielding structures of organization we’ve created, wondering what happened. What happened to effectiveness, to creativity, to meaning? What happened to us? Trying to get these structures to change becomes the challenge of our lives. We draw their futures and design them into clearly better forms. We push them, we prod them. We try fear, we try enticement,. We collect tools, we study techniques. We use everything we know and end up nowhere. What happened?
From A Simpler Way, Margaret J. Wheatley and Myron Kellner-Rogers
Wheatley and Kellner-Rogers’ article at http://www.margaretwheatley.com/articles/life.html further develop some of the organizational implications of CAS in a very readable and humanistic way. They propose four basic principles: 1) Participation is not a choice. 2) Life always reacts to directives, it never obeys them. 3) We do not see “reality”. We each create our own interpretation of what’s real. 4) To create better health in a living system, connect it to more of itself.
To quote the article:
We have been careful to state principles here rather than techniques or step-by-step methods. This is in keeping with our understanding of how life organizes. The organizations that life creates are highly complex. They are filled with structures, behavioral norms, communication pathways, standards and accountabilities. But all this complexity is obtained by an organizing process that is quite simple, and that honors the individual’s need to create. The complexity of a living system is the result of individuals freely deciding how best to interpret a few simple principles or patterns that are the heart of that system. These simple patterns of behavior are not negotiable and cannot be ignored. But how they get interpreted depends on the immediate circumstance and the individuals who find themselves in that circumstance. Everyone is accountable to the patterns, but everyone is free to engage their own creativity to figure out what those patterns mean. This process of organizing honors individual freedom, engages creativity and individuality, yet simultaneously achieves an orderly and coherent organization.
From such simple patterns complex organizations arise. Structures, norms, networks of communication develop from the constant interactions among system members as they interpret the patterns in changing circumstances. Individuals make decisions about how best to embody the patterns, and an organization arises. Sophisticated organizational forms appear, but always these forms materialize from the inside out. They are never imposed from the outside in.
APPRECIATIVE INQUIRY
Appreciative Inquiry (AI) is both a philosophy and an applied method to achieve positive change. The concept was introduced in 1987 by David Cooperrider, and began getting widespread attention in the mid-1990’s. Since then it has been widely used in all kinds of settings, from churches and communities to business and even the military.
AI writer and consultant Jackie Kelm describes it as ” a way to discover … things that provide a foundation for building greater effectiveness and satisfaction as a community of people. It is a shared awakening of hope and desire for a future possibility that did not exist or had not been shared before.”
Decades before Cooperrider coined the term, the basic philosophy behind Appreciative Inquiry was articulated by Albert Schweitzer:
Judging by what I have learned about men and women, I am convinced that far more idealistic aspiration exists than is ever evident. Just as the rivers we see are much less numerous than the underground streams, so the idealism that is visible is minor compared to what men and women carry in their hearts, unreleased or scarcely released. Mankind is waiting and longing for those who can accomplish the task of untying what is knotted and bringing the underground waters to the surface.
The fundamental assumptions of Appreciative Inquiry include:

• 1. In every organization, something is working well already.
• 2. What people anticipate determines what they will find
• 3. People and organizations are like poetry, open to infinite interpretations
• 4. Positive change requires viewing people and organizations positively
• 5. The very act of asking questions influences the organization

In short, organizations create their own reality, constantly making themselves in their own image. (In CAS terms, this is another way of explaining how a stable “attractor state” may be sustained in an organization.)
Traditional paths to positive change involve identifying problems and barriers and then looking for solutions, but according to the AI viewpoint this simply reinforces the organization’s identity with those problems. Dissatisfaction with the current state is an important clue to a desired future state, but the first step in the AI change process is to begin exploring what is good and valuable and working well already. Engaging as many organization members as possible in one-on-one interviews, an AI practitioner gets people talking about past successes and future dreams, then uses the positive energy generated to facilitate brainstorming about ways to acheive goals while keeping what’s best from the past . Just as in the CAS model, the future state is not determined ahead of time but emerges from the hopes and dreams of the individuals involved. If there is enough energy generated in that direction, the thinking goes, the system can enter into a more positive state and stay there.
Some critics of AI ask how it’s possible to achieve goals without looking at barriers, or whether this isn’t just trying to paste a smiley face on everything. People who are committed to AI respond that it’s a choice of perspective, that beneath a stated problem there is always an assumption about how things could be better. They say that when you have more of what you want, there’s naturally less room for what you don’t want. A thorough Appreciative Inquiry initiative is likely to be very time-consuming, since it requires large numbers of individual interviews, extensive communication of the results, and followup brainstorming meetings. It requires an outside consultant, which can be expensive, and that person must be highly skilled at building trust between her/himself and individuals at all levels of the organization. Organizational leadership must be personally committed to the power of AI principles, and willing to relinquish control of the outcome, since dreams and ideas from all levels of the organization are equally important to shaping the future. (The subject of leadership, and how it is gradually evolving to support new organizational paradigms, deserves an article in itself.)
CONCLUSION
There are no magic bullets. We need multiple perspectives to understand human systems, especially ones as extremely complex as an orchestra organization. Trying to integrate all those perspectives can be exhausting and frustrating. Nevertheless, the concepts in the present article are a very useful addition to the repertoire. I trust that interested readers will make their own conclusions about how they might apply in the orchestra world. What if organization members at all levels were to give up on the impossible task of controlling outcome and simply work to create the right context, trusting the system’s self-organization to take it from there? What if we could create momentum in the right direction by focusing the power of our attention on the things that we do well and the things we want more of?
BIBLIOGRAPHY
Morgan, G. (1997) Images of Organizations Thousand Oaks, CA: Sage Publications
Hammond, S. and Royal, C. ed. (1998) Lessons from the Field: Applying Appreciative Inquiry Plano, TX: Practical Press
Websites: