Leaders are often cautioned to watch their actions and behavior because it sets an example and gets replicated through the organization. Which begs the question: why do people copy leaders? The common explanations tend to be psychological.
But it goes beyond simple carrot and stick notions from behaviorism. There's a simple logical explanation based on a deeper understanding of organizations seen through the lens of complexity sciences.
The systems and unspoken rules and norms that we work within, end up influencing our actions a lot more than just plain psychology. We are independent agents, trying to optimize for the best outcomes, who are in effect changing the game as we play it. And this game is being played inside what's called a complex adaptive system.
What are complex adaptive systems
Most of us, including organizations, intuitively recognize complexity but don’t necessarily know how to operate in it. Complexity is different from plain “complicated”. It's also different from chaos sciences.
The simple answer is that chaos deals with situations such as turbulence that rapidly become highly disordered and unmanageable. On the other hand, complexity deals with systems composed of many interacting agents. While complex systems may be hard to predict, they may also have a good deal of structure and permit improvement by thoughtful intervention.
— Robert Axelrod, Michael Cohen in Harnessing Complexity
There are dynamics unique to complex adaptive systems. This post is not a definitive one on complex adaptive systems, but the book Harnessing Complexity is a great introduction to basic concepts of complexity that are essential to understanding how organizations work and operating within them.
Axelrod and Cohen start off the book by asking one simple question:
In a world where many players are all adapting to each other and where the emerging future is extremely hard to predict, what actions should you take?
This is the question everyone faces when working in organizations and given the nature of careers. As much as we would like to think otherwise, the trajectory of both our companies and our own careers are anything but predictable. So how do we go about optimizing when there are no clear answers?
One place to look is to understand the nature of complexity. Every organization in effect is a complex adaptive system and we are agents operating within them.
Whenever we are interested in designing something new (such as a product or sales strategy), or when we are contemplating a possible change in a policy (such as new store opening hours), we are considering interventions in a system. But what might make a system we are interested in complex?
… a system is complex when there are strong interactions among its elements, so that current events heavily influence the probabilities of many kinds of later events. A major way in which complex systems change is through change in the agents and their strategies.
In Complex Adaptive Systems there are often many participants, perhaps even many kinds of participants. They interact in intricate ways that continually reshape their collective future. New ways of doing things— even new kinds of participants—may arise, and old ways—or old participants—may vanish. Such systems challenge understanding as well as prediction.
These difficulties are familiar to anyone who has seen small changes unleash major consequences. Conversely, they are familiar to anyone who has been surprised when large changes in policies or tools produce no long-run change in people’s behavior.
When a system contains agents or populations that seek to adapt, we will use the term Complex Adaptive System. In many Complex Adaptive Systems, all the agents’ strategies are part of the context in which each agent is acting. This makes it hard for an agent to predict the consequences of its actions and therefore to choose the best course of action.
Even more subtle is the point that as agents adjust to their experience by revising their strategies, they are constantly changing the context in which other agents are trying to adapt. For example, workers in a company might be learning better ways to produce a product. Each change of strategy by a worker alters the context in which the next change will be tried and evaluated. When multiple populations of agents are adapting to each other, the result is a coevolutionary process.
What makes prediction especially difficult in these settings is that the forces shaping the future do not add up in a simple, systemwide manner. Instead, their effects include nonlinear interactions among the components of the system.
Why look at organizations as complex adaptive systems
The Complex Adaptive System approach is a way of looking at the world. It provides a set of concepts, a set of questions, and a set of design issues.
Why might this perspective and its associated vocabulary be useful for deliberations over action in settings whose consequences are hard to predict? Complexity research deals with systems that are hard to control, and much of it has gone on in fields that seem far from policy or design concerns. … However, many of the same dynamics are involved in social issues. … Social systems exhibit dynamic patterns analogous to physical, biological, and computational systems.
Complexity research gives us a grounded basis for inquiring where the “leverage points” and significant trade-offs of a complex system may lie. It also suggests what kinds of situations may be resistant to policy intervention, and when small interventions may be likely to have large effects. For guidance in designing actions, such insights into the right questions can be very valuable. They can be valuable even if the theories are too multiple and too preliminary to support any claim that a theory of complexity implies any sharply etched expectation about a future scenario and how a particular action will guarantee it.
It is our argument that principles derived from working with complexity problems shed valuable light on the issues confronting policy makers and designers.
Complexity is a potent framework to understanding organizations and optimizing our actions within them. Which leads us to our main question: why do we copy leaders?
Why leaders get copied – intelligence as acting foolishly
Put simply, the world is not as predictable as we would like to be. We do not know beforehand what will work and what won't. Accepting this reality, but also designing actions that increase our chances of success is what James March calls the technology of foolishness.
In the 1970s, James March began to write articles about a provocative topic: “the technology of foolishness” . He forced into the open an issue that remains hidden in a more conventional view of choice or decision making in social systems: the hard reality that the world in which we must act is often beyond our understanding. He began to draw out the implications of this fact when others were mostly in denial. It implies that each action we take is partly an instrumental step and partly a learning experience.
We copy leaders because it's the most logical approach to increase our probability of favorable outcomes when operating in environments of high uncertainty and no clear cause and effect. Each time we copy, we are essentially taking action in uncertainty, which creates more feedback and intelligence about the system we are operating in. This in turn informs future actions.
In the ambiguous and hard-to-predict world of a Complex Adaptive System, agents often don’t know what criteria of success they should use or how to evaluate the strategies they could select. This is especially important in an age of uncertainty and rapid change. When adaptive agents live in a rapidly changing environment, they tend to look to other agents to see which performance measures tend to work and which ones tend to fail.
When agents are not able to predict the effects of various possible courses of action, they may resort to imitating the observable behavior of agents who seem to be successful, or who at least have more experience with the new environment. Imitating others who are successful or experienced is a form of implicit attribution of credit that certainly has its disadvantages. When features that are copied are only superficially relevant, the results can be wasteful or even comical. Nevertheless, following the practices of those with more experience or success is often a good strategy in an uncertain world.
There are three basic reasons a leader in a formal organization or other social system is especially likely to be copied.
First, a leader can sometimes set standards that provide incentives for others to copy.
Second, a leader’s actions or performance measures are typically seen to be successful and hence worth emulating.
Third, a leader may set an example that helps establish beneficial norms in a community.
Leadership in setting a standard can cause others to go along for their own reasons. Consider the case of Norway as a country that writes much of the world’s maritime insurance. When the standards body in Norway set certain regulations for insuring oil platforms, the makers of oil platforms had an incentive to build in ways that met those standards. Thereafter other marine insurers tended to gravitate toward similar regulations. Norway’s regulations helped shape the industry in ways that led other maritime insurers to copy their visible behavior.
The emulation of a leader need not be based on a full understanding of how the emulation will help. Other agents may wish to emulate the actions or performance measures of a visibly successful leader in the hopes that what worked for the leader will work for them.
…. For example, Gandhi’s criterion of nonviolence was advanced throughout the world by the success its practitioners achieved in winning India’s independence from Britain. Gandhi’s leadership was successful in large part because he visibly embodied the very values he was advocating. This led others to emulate not only his tactics but also his values.
Visible leadership can also be exercised by setting an example that helps establish beneficial norms in a community. In Complex Adaptive Systems, norms are often important regulatory mechanisms. Central monitoring and control can be difficult when many agent interactions are widely distributed across physical or social spaces.
Criteria that the agents themselves apply are a very attractive alternative. Especially when they become internalized, norms regulate not through fear of consequences but through the belief that some actions are right and others wrong. This is extremely important when monitoring by central authorities is costly or intrusive. Moreover, once established, a norm can be reinforced and spread by dispersed agents who accept the norm and are willing to punish others who deviate from it.
- One of the key features of complex systems is the lack of clear cause and effect. Instead of one way relationships, there are causal loops that influence and build on each other. We assume linear causality, whereas in reality it's often more circular.
- Organizational life tends to be replete with paradoxes — two opposing situations that exist simultaneously but that cannot be solved away. Recognizing these paradoxes beforehand can increase our effectiveness in operating within them optimally.
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Sources and references
- Harnessing Complexity: Organizational Implications of a Scientific Frontier by Robert Axelrod and Michael D. Cohen.
- Axelrod, Robert. “An Evolutionary Approach to Norms.” American Political Science Review.
- Influence: The New Psychology of Modern Persuasion by Robert Cialdini.
- Leading Minds: An Anatomy of Leadership by Howard Gardner.
- Chaos by James Gleick.
- March, James G.. “The Technology of Foolishness.”
- More on complex adaptive systems: https://en.wikipedia.org/wiki/Complex_adaptive_system