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February 20, 2010 17:54 MAC-US/COMI Page-iii 9780230622272_01_previii
Complexity and the Nexus
of Leadership
Leveraging Nonlinear Science to Create
Ecologies of Innovation
Jeffrey Goldstein, James K. Hazy, and Benyamin B. Lichtenstein
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Chapter 1
Introduction:
A New Science
of Leadership
During the initial panic of the “Great Recession of 2009” John
Chambers, the CEO of Cisco Systems, told the New York Times of a
crucial lesson he had learned nearly a decade before from Jack Welch
when he was CEO of GE.1Chambers had asked, “Jack, what does
it take to have a great company?” Welch responded, “It takes major
setbacks ...by that I mean, a near-death experience!”
Well, in 2001, Cisco nearly did die when the tech bubble burst
and Chambers’s leadership came under question. Yet, in 2003, when
it became clear that the company had passed the test, Welch called
Chambers and told him that he now had a great company. “It doesn’t
feel like it,” Chambers replied. But at that very moment, in respond-
ing to Jack Welch, he finally understood what Welch had meant back
in 1998: organizations that face and survive serious challenges can
emerge stronger. This, of course, is only if they don’t fail!
What distinguishes companies that emerge stronger from those
that fail? The key lies in how innovation supplies additional capabil-
ities for adroit action in the face of unexpected and rapidly changing
conditions. Firms that can’t innovate go the way of dinosaurs. As a
major ingredient in adaptability, innovation means much more than
introducing new products or services, although without those no
organization can compete in this economy. Truly adaptable orga-
nizations must also innovate their practices, processes, strategies,
and structures so that their internal capacities become a match
for turbulent environmental conditions. Staying competitive in the
twenty-first century requires a higher level of innovation and adapt-
ability than most of us have ever seen, and the bar keeps rising.
Achieving this is simply not possible through traditional top-down
February 20, 2010 12:46 MAC-US/COMI Page-2 9780230622272_02_ch01
2COMPLEXITY AND THE NEXUS OF LEADERSHIP
management fiats, nor by “shared” or “distributed” leadership that is
being sold by so many books and consultants these days.
So, how can such high levels of innovation be achieved? This book
provides a new answer to that critical question by showing how lead-
ers, guided by the insights coming out of complexity science, can
create ecologies of innovation throughout their organizations. Lead-
ers in an ecology of innovation encourage and support “experiments
in novelty,” building new organizational pathways that allow these
experiments to materialize into novel offerings and improvements.
Complexity science thus puts leaders in a greatly enhanced posi-
tion to help their organizations effectively navigate critical periods
of growth and change.
A Complexity Science of Generative
Leadership
Our book presents a host of insights coming from complexity sci-
ence about how ecologies of innovation can be created. Over the last
decade or so, nonlinear science researchers have developed tools and
concepts that more accurately explain how organizations operate,
how leaders can be more effective within them, and how innovation
really comes about.
In particular, complexity science shows how the typical focus on
“heroic” and charismatic leaders can result in a lack of innovation in
modern organizations.2In contrast, we reframe “leader” and “leader-
ship” as referring primarily to events rather than to people. Through
a series of interactions over time, leadership events alter the under-
lying framework of engagement. They change the rules by which
individuals interact, influencing the ends to be achieved, such as
where a work group is headed, as well as the means by which it
gets there.
A complexity science – based view sees leadership as an influ-
ence process that arises through interactions across the organization:
leadership happens in “the space between” people as they interact.
Through influential interactions, which are happening all the time
in every corner of the organization, novelty emerges and is enacted
in unique and surprising ways. This means that the true catalysts
of innovation are the webs of relationships—in the nexus of inter-
actions that connect members to each other and to others in the
environment.
We are using the term “generative leadership”3to highlight that
the process of innovation is not led by any one individual but
emerges through an unfolding series of events at every level of the
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 3
organization. Generative leadership focuses on the mutual influence
that occurs within every exchange. Accordingly, rather than concen-
trating on how a supervisor expresses influence over an employee,
generative leadership sees them both as expressing leadership. More-
over, generative leadership refers to capturing the benefits of this
mutual interplay as a generative process—it spawns new opportuni-
ties that increase the organization’s potential for novelty, flexibility,
and growth. As a process that builds progressively, generative leader-
ship tunes into patterns of interaction rather than specific “one-time
moves” that a manager may initiate and carry out.
Generative leadership does not wait fatalistically for the unex-
pected to happen, but instead actively participates in and coevolves
(more on this term later) with the environment and the future. Com-
plexity and the Nexus of Leadership shows the usefulness of this new
understanding of leadership through research findings from com-
plexity science and through many cases and examples from a wide
range of corporations, entrepreneurial start-ups, social ventures and
NGOs, and governmental agencies.
Complexity Science Empowers Leadership
One of the most important takeaways from this book will be just
how empowering are the new advances in complexity science for
leadership. What we mean by the term “complexity” is not the
same as what most managers are taught to fear, and therefore try to
undo. In technical terms, “complicated” describes, for example, the
design and manufacture of a jumbo jet, an exceedingly difficult task
involving up to two million separate parts and untold operations.
In contrast, “complex” has to do with the interactions in the system,
through which something new emerges, such as norms in a work
group or a groundswell of momentum for a new enterprise. Until
recently the differences between complicated and complex were not
well understood; as a result they have often been treated in the same
way, as if the same process should be used to “deal with” situations
that are complicated or complex. Business schools justified this by
treating organizations as if they were machines that could be ana-
lyzed, dissected, and broken down into parts. According to that
myth, if you fix the parts, then reassemble and lubricate, you’ll get
the whole system up and running. Butthisisexactlythewrongwayto
approach a complex problem.
In this book we show precisely why this is wrongheaded: it misses
the fact that under the right conditions a complex system can adapt,
whereas a piece of machinery cannot. A complex system, through its
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4COMPLEXITY AND THE NEXUS OF LEADERSHIP
own internal processes, can actually change itself so as to generate
better outcomes. No one would expect an aircraft, no matter how
complicated the design, to reconfigure itself so that it flies faster or
operates more efficiently! And yet, organizations do these kinds of
things all the time. This is a critical difference between complex ver-
sus complicated systems that traditional approaches miss entirely.
Instead, they talk about performance and efficiency and then add
as an afterthought, “Oh yes, you need innovation also, so do that
too.” Although complex systems are often intricately entangled and
complicated with all sorts of factors and people and systems, it
is their complexity and not their complicatedness that makes them
adaptable.
There is one more crucial difference. In a complex system, but
never in a complicated one, even a small number of people, work-
ing well together, can make a major difference that goes beyond any
one of their capabilities. Complexity science empowers individuals
by demonstrating how they can alter a system, collectively making
new things happen. What is exciting about the advent of complexity
science is that it helps explain, for the first time, why some organiza-
tions are able to adapt and change and grow, and why others fail the
crucial test that Jack Welch posed to John Chambers. In this book
we will tell you how you can make this critical difference.
The Adaptive Potential of Complexity
Complexity science empowers leadership in another way: it presents
an active and constructional model of leadership based on a highly
engaged view of mutuality, interdependence, and shared account-
ability. By “active” we distinguish this book from a spate of “com-
plexity” texts that promulgated a laissez-faire view of leadership; by
“constructional” we mean the hands-on building up of ecologies of
innovation, the construction of more effective social networks, and
the search and amplification of experiments in novelty, which result
in the emergence of innovations.
This sharply distinguishes our book from the so-called self-
organization approach to leadership—the laissez-faire style that has
only the most superficial connection to the science of complex
systems. This facile notion of self-organization was linked to a
somewhat absurd claim: somehow, by dismantling hierarchically
directed command and control structures, the organization will
spontaneously reorganize “on its own,” resulting in positive direc-
tions for it. In fact, rigorous complexity science research has borne
out the opposite conclusion, namely, that any positive result from the
emergence of innovation requires both bottom-up and top-down
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 5
influences from proactive leadership events. In contrast, tearing
down hierarchical structures can easily lead to a morass of unantic-
ipated outcomes, many of which are much worse than what existed
before.
Finally it is important to note that organizations have always
been complex. What has changed is our ability to understand
them as complex systems and thereby influence them. Complexity
means that “system components”—individuals, or more generally
“agents”—each with a different perspective and information, inter-
act with each other in a mode of mutual influence. In this mode
complexity arises when even two agents interact, since their unique
information and perspective generates difference, and difference leads
to unanticipated and novel outcomes. Of course, this is magnified
many times across the interactions of 20 or 100 or 1,000 people.
Everyone who works in an organization intuitively realizes that
social interactions are complex in this way, and yet business schools
and most so-called leadership experts have traditionally ignored this
obvious fact.
A simple example will clarify the nonlinear and non-proportional
effects of this kind of complexity. In a social network with two peo-
ple there are two connections, one in each direction. With three
people there are six possible connections, each person to two others.
Five people have 20 connections, eight people have 56 connections.
Notice how this buildup of connectivity is not linear; the number
of connections increases much faster than the number of individu-
als. For example, a social network with 100 individuals yields 9,900
possible connections, any number of which can come together to
influence the outcome.
This view of nonlinearity helps explain some powerful ele-
ments of complex systems. First, as we’ve said, complex systems
are not linear—hence the term “nonlinear” in our title—because a
given cause does not lead to a proportionate result. Second, com-
plex systems are not easily predictable, since what emerges from
their interactions is something more than a simple aggregation of
their properties. Third, although complex systems are undoubtedly
stochastic (i.e. irregular), they are not random since dynamical pat-
terns are discernible, and these can be acted upon by generative
leadership. Indeed, if randomness was the final message of complex-
ity, then this book should be about how to teach leaders to become
better gamblers!
It is the very uncertainty, unpredictability, and uncontrollabil-
ity of organizational processes that signal the adaptive capability
of complex systems; their capacity for the emergence of novel
practices, processes, and routines is at the heart of an ecology
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6COMPLEXITY AND THE NEXUS OF LEADERSHIP
of innovation. Because of this capacity for adaptability, the com-
plex systems that are of interest are often described as complex
adaptive systems. Examples of complex adaptive systems include
living organisms and ecologies, healthy immune systems, thriv-
ing economies, and the sustainable functioning of organizations,
whether entrepreneurial start-ups, nonprofit entities, or large insti-
tutions and corporations.
In a business or other organization, a complex adaptive system
is composed of individuals—semiautonomous agents—who inter-
act according to certain rules. Each individual gathers information
about the internal workings of the organization as well as the
environment according to that person’s own position and history.
Individuals in a complex system are necessarily diverse in form, in
capability, and in the information they hold and use. Moreover, each
adapts more or less effectively by gathering information, learning
from others, and changing their own rules or mental models when
possible. Whether a group of these learning individuals somehow
translates into an organization that is adaptable, though, is a differ-
ent matter. This is where generative leadership can make the critical
difference. In this book we show how generative leadership can build
and enhance this capacity for adaptability.
The Contribution of Nonlinear Science
We are claiming that insights from complexity science have the
power to reframe leadership and transform organizations, but only
when these insights are properly understood. Unfortunately, most
leadership or management books that have appealed to complexity
science have presented a narrow understanding of complex system
dynamics, on the basis of a highly stylized interpretation of a few
intriguing outcomes. The result is merely a set of metaphors that fail
to deliver any sustainable advice to managers and executives dealing
with rapid change.
Furthermore, many previous books in this genre were insult-
ing to the reader by aiming for a lowest common denominator of
intelligence and expertise. In contrast, we are assuming that our
readers are intelligent, with proficiencies based on years on hard
work and difficult decision making. This means that in order to
provide the accuracy and value you deserve, the material in this
book requires thoughtfulness and imagination. Rather than mask-
ing the inherent complexity of organizations by using simplistic
interpretations, we will take this difficulty on directly through clear
descriptions and vivid examples, visual diagrams, and alternative
ways of understanding.
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 7
Systems Theory
Social Networks
Artificial Life
Evolutionary
Biology
Complexity
Science
Solid State/
Condensed Matter
Physics
Evolutionary
Systems
Nonlinear Dynamical
Systems Theory
Computational
Theory Synergetics
Non-Equilibrium
Thermodynamics
Biological Emergence
Dynamical
Systems
General Systems
Theory Fractal
Geometry
Chaos Theory
Catastrophe
Theory
Self-Organized
Criticality
Cybernetics
Information
Theory Artificial
Intelligence
Algorithmic
Complexity
Autopoiesis
Game Theory
Cellular Automata
Agent-Based Models
Artificial Societies
Figure 1.1 Scientific and Mathematical Fields Making Up Complexity
Science
To begin, we provide a glimpse of what complexity science
encompasses. The various fields making up complexity science are
presented in figure 1.1. As this diagram shows, the science of com-
plex systems is the confluence of a number of fields. On the far left
we see the original systems sciences of cybernetics, information the-
ory, and General Systems Theory, all of which originated around the
time of World War II. These approaches were then extended in the
1960s, 1970s, and 1980s by new theories of nonlinear dynamics in
physics and mathematics, order emergence in thermodynamics, the
advent of network science, and a great plethora of computational
simulation studies. For the past 20 years there has been a literal
explosion of complexity research due to the availability of power-
ful microcomputers and the establishment of institutes and centers
around the world that are devoted to the study of complexity science.
Rather than go into the history of complexity science, suffice it to
say that in this book we draw on fields that are situated roughly to
the right of the center of this whale-shaped diagram. Whereas virtu-
ally all other complexity books make use of perhaps one or two fields,
our treatment is based on relevant insights from nearly a dozen fields
of complexity science. The result is a robustness of theory and appli-
cation that has a proven track record of success. We now turn to a
summary of some of the key themes that are illuminated throughout
the book.
Complexity and the Nexus of Leadership:
Core Themes
To give you a sense of what’s to come, we present the main themes
of the book, some of which refer to specific chapters and others
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8COMPLEXITY AND THE NEXUS OF LEADERSHIP
that are interwoven throughout the book: Ecologies of Innovation;
Interaction Resonance within Social Networks; Differences, Infor-
mation, and Novelty Generation; Critical Periods and their Potential
for Innovation; Emergence; and Boundaries and Constraints.
Ecologies of Innovation
At the heart of our complexity view of leadership is the idea of an
ecology of innovation. The science of ecology consists of the study of
interactions between ecosystems, eco-subsystems, and their environ-
ments. By focusing on the network of interrelations making up an
ecosystem within a specific area, ecology employs a whole-systems
viewpoint. In an important sense, an ecosystem is the most accu-
rate picture of what a complex, nonlinear, adaptive, and interactive
system is all about. Sub-ecosystems are the components in interac-
tion with each other and with other subsystems in the environment;
these interactions supply the nutrients, building materials, wastes,
and information that get transmitted from system to system in a vital
exchange. No sub-ecosystem can survive on its own. Instead, the vast
set of interchange and exchange that connects one to another enables
the entire ecology to thrive.
It is within this vast web of interconnectivity that we see all the
features of complex systems:
• Micro-level diversity supplying seeds of novelty
• Experiments that move parts of the system away from normal
routines
• Intricate networks connecting interdependent subsystems to
one another
• Innovations conferring new functionalities that enhance adapt-
ability to unexpected changes or “jolts” from the environment
• Critical periods of instability that allow for substantive trans-
formations of behaviors and dynamics
Recent complexity science and ecology research has uncovered some
key patterns in ecologies—regularities that help sustain a thriv-
ing ecosystem within a continually changing environment—insights
that we describe in detail in the next chapter.
Since ecologies are driven by all of the exchanges, interchanges,
interactions, and connectivities existing between its subsystems,
whatever is essential takes place at these interfaces. That is why inter-
actions, as first spelled out in Chapter 2, are so important to our
approach. This concentration on interaction should not be taken
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 9
merely in the sense of distributed control, but instead highlights
how innovation itself relies on the “space” between systems as where
novelty has its most fertile environment.
By an ecology of innovation we recognize that every organiza-
tion occupies a niche within its communities, customers, suppliers,
strategic partners, and competitors, and this places constraints on the
organization’s choices. This means that information is being discov-
ered all of the time, by many people in many specific situations. The
information first appears in a specific context, and it is often difficult
to recognize and comprehend and is easy to lose. This prompts the
question of how an organization can learn to distinguish signals of
imminent change from the constant level of noise inherent in day-
to-day activity. That is one of the key themes of this book, and one
of the main areas in which complexity science can help all of us. In
chapters 2, 5, 6, and 7 we provide ways to think about this issue and
tools to help individuals do exactly this.
An ecology of innovation offers one more conceptual advantage:
it can be understood at many different scales of resolution. For exam-
ple, a desert can be viewed at the scale of tiny lichen on shaded rocks
or on the wider scale of small cactus growing near dried rivulets or
on a wider scale of small rodents scurrying among the rocks on the
north side of desert mountains away from the sun or on the larger
scale of the slow changes in the weather that may occur as one season
haltingly changes into another. The same is true of organizational
ecologies. Thinking and acting can occur at many different levels of
scale, and since complex systems are inherently nonlinear, what hap-
pens on a microscale may have a large impact on a macro- or even
collective scale.
Interaction Resonance within Social Networks
Atthecoreofecosystemsarepatternsofinteractions—thevital
exchanges—that connect all the subsystems together. In complex-
ity science, interaction is a web of positive and negative feedbacks
among components. Because a complex system is composed of
interdependent, interacting subsystems, information about the func-
tioning of the system is distributed throughout the networks of
connection. This is why generative leadership focuses attention on
the nexus of relationships linking individuals within the social net-
work. This nexus of relations is the source of influence, the driver of
innovation, and the regulator of change.
In social systems, interaction shows itself in the prevalence of
social networks that connect the components of any system, a topic
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10 COMPLEXITY AND THE NEXUS OF LEADERSHIP
we explore in depth in Chapter 7. Every social network has a struc-
ture that reflects the configuration of how people are linked with
one another. These networks extend not only within an organization
but throughout its entire ecology, as well as into the environment.
Arguably, an individual’s professional success in business and in
other fields is determined as much or more by the scope and quality
of their network connections than by their individual competence.
These networks of interaction, although largely ignored in Business
Schools, are central to our view of generative leadership.
Although communication has long been an important topic in
leadership practice and management education, the specific nature
of how information can be enriched as it is exchanged has not
received the attention it deserves. From our complexity science
perspective, we are calling the process of information enrichment
interaction resonance. It is largely through interaction resonance that
the kind of micro-level diversity that we discuss in the next section
expresses itself as those experiments in novelty that are at the core
of innovation. Interaction resonance is described in Chapter 2, and
it is a theme that winds its way through our entire presentation of
innovation, particularly in Chapter 3, in which we suggest that inter-
actions are central to “critical periods” of change, and in Chapter 7’s
explanations of social networks, which are the context in which
interaction resonance takes place.
Differences, Information, and Novelty Generation
One of the hallmarks of a complex system is its heterogeneity, that is,
the vast diversity of components, agents, and parts, each involved in
an ongoing variety of distinct interactions with the others. These dif-
ferences create novelty since the interaction of two identical things
cannot generate something new. We conceive of organizations and
their leadership as complex systems that operate from as well as
produce great differences, which in turn allow for innovations to
emerge.
In the original version of information theory, information referred
to the “important” bits of a message in a communication channel, as
opposed to “noise.” Later, the idea of information was generalized to
be patterns of redundant order mixed with elements of surprise, thus
expanding information to include the differences among a range of
patterns. Information in social systems plays a role similar to the role
played by energy in physical systems, namely, it is the “life blood”
that flows through organizations and connects them to systems
in their environment. In this way information is meaningful—it
literally carries meaning throughout a system.
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 11
In organizations, meaning emerges through the differences in
members’ backgrounds, skills, opinions, and perspectives; these dif-
ferences help drive innovation, a theme we’ll return to in Chapter 3.
Our use of the term “information” throughout this book thus
includes formal facts contained in textbooks and reports but also
surprises from events, experience, or experiments.
Pushing this analogy further, the catalyst for innovation lies in
deviations from what is expected, that is, experiments in novelty
reflecting departures from the currently accepted and conventional
ways of functioning. These experiments are constantly going on in
organizations, although such deviations are typically unnoticed or
marginalized. Complexity science has shown that this micro-level
diversity, when it is noticed, amplified, and disseminated by genera-
tive leadership, can emerge as novel patterns, practices, and strategies
that can improve and transform organizations. These emergent phe-
nomena, which we discuss in chapters 3, 4, and 5, introduce new
qualities into the system that are neither expected, predictable, nor
deducible from the preexisting components.
An issue, therefore, for leadership working with complex systems
is to determine which micro-level deviances possess a potential for
significant emergent innovation. In chapters 5, 6, and 7 we describe
several ways in which generative leadership can approach this issue,
including a type of social network called “intercohesion” which
makes it more likely that micro-level diversity with the potential for
innovation is recognized and amplified.
In Chapter 6 we describe a particular kind of difference with
innovative potential, termed “positive deviance,” a unique frame-
work that links the constructive term “positive” with the usually
negatively term “deviance.” We show that major innovations and
transformations have, in one way or another, relied on radical
departures from what is expected, and these are justifiably exam-
ples of “positive deviances.” Leadership can use the tool of positive
deviance as social intervention that helps social systems identify and
amplify novel experiments that have previously gone unnoticed, but
whose problem-solving and opportunity exploitation potential can
be unleashed.
Critical Periods and Their Potential for Innovation
Another feature of complexity science, and an important theme in
this book, is how complex systems can dramatically transform dur-
ing critical periods. We use the term “criticalization” to refer to major
transitional periods, which have important implications for gen-
erative leadership. Complexity science insights from criticalization
February 20, 2010 12:46 MAC-US/COMI Page-12 9780230622272_02_ch01
12 COMPLEXITY AND THE NEXUS OF LEADERSHIP
are drawn from phase transitions – when matter transforms from
one state into another, the emergence of new dynamics – when
the connectivity structure of a social network is changed, the emer-
gence of new order in self-organizing physical systems – when some
critical parameter value is reached, and the emergence of new attrac-
tors – when nonlinear dynamical systems bifurcate or split into two
separate stable states. We will be alluding to all of these critical
phenomena in chapters 3, 4, and 7.
Customarily, criticalization is understood as a system that moves
away from equilibrium or normative functioning, and in so doing
leaves behind stability while opening to novel and unstable states.
These conditions of disequilibrium and instability may be unset-
tling, but they are necessary for the complex system to undergo deep
transformation. Indeed, a system ensconced in a stable condition
will reject any fluctuations that may lead to novelty, and as quickly as
possible it will return to its original stable state. In contrast, complex-
ity science shows that it is only when a system is unstable—especially
in a period of criticalization—that internal changes can move it to a
new regime of activity.
Criticalization is the essence of the anecdote at the beginning
of this chapter: as Jack Welch told John Chambers, critical peri-
ods are what define an organization. They separate the companies
that are truly great from those that merely survive. It is during crit-
ical periods that the strength and proficiencies of an organization’s
leadership are truly tested, and it is during these periods that the
organization most needs its leadership to step up to the task. Com-
plexity science shows that the key difference between success and
failure is generative leadership, which effectively guides an organi-
zation to embrace the “critical period” instead of trying to avoid its
effects. In Chapter 3 we describe how this was done in the transfor-
mation of IBM under CEO Lou Gerstner4as well as at Imagitas and
Oracle, and in Chapter 5 we describe the various strategies leading
to expansion at Starbucks when it engaged several critical periods.
Change management consultants sometimes describe the need
for leaders to “manufacture a crisis” as a prerequisite to a success-
ful change management effort; however, in our experience we have
found that employees and all the other stakeholders see through such
artificial moves. Instead, generative leadership positions the orga-
nization so that it can recognize and take advantage of significant
changes in the environment. A key task of generative leadership at
every level is to enable and encourage a vital connection between
an organization and its changing environment; it is only when
such connections are engendered that critical periods can offer
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 13
the potential for renewal and emergence that are the hallmark of
long-term success.
Successful criticalization leads the organization into a stronger
era—the company becomes better matched to its markets and better
able to change with them in the future. It requires that the orga-
nization develop new capabilities that facilitate a new pattern of
interaction between its members. If used in the right way—if one
can be in a state of “surfing forever on the edge between never stop-
ping but never falling”5—then the organization has the potential to
engage in the unique process of emergence itself.
Emergence
Emergence, one of the most exciting and relevant areas of research in
complexity science, refers to the arising of novel structures, patterns,
or processes in complex systems. For example, the emergence of new
attractors is discussed in Chapter 3, the emergence of new structures
with new properties is covered in Chapter 4, and the emergence of
new forms of social cooperation in social networks is described in
Chapter 7. The study of emergence in social systems is especially
apt given the plethora of new kinds of organizational forms: joint
ventures, strategic alliances, social entrepreneurial organizations, and
other forms of collaboration.
Emergent phenomena seem to have a “life of their own,” with
their own rules and possibilities. Emergence is about the aris-
ing of the radically novel—unpredictable and not deducible from
its components; thus, emergence is the essence of innovation in
organizations. Both emergence and innovation supply additional
functionalities to a complex system, providing the system with a
much greater repertoire of possible actions and processes. Much of
the current work in complexity research centers such as the Santa
Fe Institute is built around emergence, because systems that emerge
gain a significant adaptive advantage in their environment.
Emergence comes about through a recognition, amplification,
and dissemination of those seeds of innovation that come from
micro-level diversity or experiments in novelty. Thus, a pri-
mary objective of generative leadership in facilitating emergence
is to foster and amplify novelty generation within an ecology of
innovation.
Among the different prototypes of emergence found in complex-
ity science research that we describe in Chapter 4, we are especially
attentive to the “dissipative structures” model studied by Nobel lau-
reate Ilya Prigogine through nonequilibrium thermodynamics and
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14 COMPLEXITY AND THE NEXUS OF LEADERSHIP
the German physicist Hermann Haken in his School of Synerget-
ics, biological emergence such as found in Lyn Margulis’s idea of
“symbiogenesis,” and social emergence through the formation of
cooperative teams and similar phenomena.
As we have explained, earlier approaches to emergence in orga-
nizations strongly coupled it with a particular notion of self-
organization understood as a supposedly spontaneous process. This
view, however, resulted in the mistaken belief that leaders could be
passive and simply allow emergence to take place, once command
and control mechanisms were relaxed. More rigorous research and
experimentation have proven that emergence hardly comes about
spontaneously—instead, it demands rigorous containing, constrain-
ing, and constructional operations. Accordingly, our interpretation
of leadership’s role in emergence is not passive, but instead is active
and generative.
Boundaries and Constraints
One counterintuitive result from complexity science is that adapt-
ability can emerge only if there are constraints or boundaries that
consistently operate on the choices and actions of the individuals
in the system. A good example comes from complexity researcher
Peter Allen, whose longtime studies of fish populations in the North
Atlantic and showed that boundaries and constraints in the ecosys-
tem enabled many new species to develop and persist. He called this
effect “micro-diversity” and claimed it was critical to the ecosystem’s
ability to respond and adapt to change.6Certain species did better
under changing conditions, whereas a previously dominant species
might flag under the change. However, since one replaced the other
in the food chain, the ecosystem as a whole adapted and continued
to prosper, albeit with a different mix of species.
Similarly, it takes a constrained complex system to encourage and
maintain the information differences within individuals. These con-
straints, from external boundaries or between functions, act like the
nooks and crannies in the seabed of the North Atlantic, serving to
protect and nurture the ecology’s most important resource, namely,
informational differences.
If not for constraints of some kind, organizational members
would not be motivated to organize in new and different ways, and
no new structures would emerge. An example is the implementation
of Sarbanes-Oxley reporting requirements, or any law or regulation
that limits the degree of freedom in which the organization and
its members can operate. New routines and procedures have had
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 15
to emerge to address these new constraints, and these in turn have
changed other aspects of the organization so that the process could
be supported effectively.
In a similar vein, for adaptability to emerge in a complex sys-
tem, the right context is also important to the mix, a topic that we
discuss in Chapter 3. For generative leadership, context is as impor-
tant as content. The distinction between context and content can
be understood through an analogy from semantics.7In the context
of everyday talk, a “daughter” is a female descendant and “left” can
mean, in political discourse, the more liberal point of view. A com-
ment such as “the daughter of that family tends to veer to the left”
has a rather unequivocal meaning: the female descendant of that
family has political leanings that are more liberal than conservative.
But in a different context such as nuclear physics, “daughter” refers
to the immediate product of radioactive decay of an element, and
“left” is a direction, not a political stance. In this context, a com-
ment such as “the daughter of that family tends to veer to the left,”
made by a nuclear physicist to her colleague, means that a “family”
of elements undergoing nuclear decay tends to move toward the left
side of the experimental screen.
Most managers learned to lead through interventions that are
aimed at directing and controlling followers’ activities. In contrast,
generative leadership is more interested in the context or parameters
of organizing, the internal and external organizational environment,
and the opportunities and constraints it generates. Far more than the
substance of daily tasks and goals, it is the context of organizational
interactions that determines the potential and quality of members’
contributions.
At the same time, organizations need managers and executives
to take responsibility for specific business goals and outcomes. This
presents the conundrum of how a manager may have an influence on
their part of the system while being a generative leader who allows
influence to flow throughout the entire organization. Exploring this
balance is an issue that hovers within every chapter. The suggestions
we make are put forward as avenues for reflection and action for the
thoughtful and committed reader.
Conclusion
In summary, Complexity and the Nexus of Leadership offers a view
of how individuals at all levels can make a difference in their orga-
nizations through the practice of generative leadership. The key to
generative leadership lies in creating ecologies of innovation in the
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16 COMPLEXITY AND THE NEXUS OF LEADERSHIP
workplace, in which experiments in novelty lead to innovative prac-
tices, processes, and routines, enabling an organization to become
adaptable to the unprecedented levels of change characterizing
today’s business environments.
The remainder of this book unfolds as follows: the next chapter,
Chapter 2, presents a 50,000-foot view of why organizational life has
become so difficult to navigate in recent years. With global supply
chains and Internet connectivity, the age of the stand-alone business
that runs like a machine is being replaced by one in which orga-
nizations exist in a network of partnerships that looks much more
like an ecological system than a complicated machine. We draw on
complexity research to explore how ecologies work, as well as the
critical role played by interaction resonance—our term for effective,
two-way information flow—the key enabler of adaptation within
ecologies. After this high-level overview, we proceed to the core of
the book, chapters 3, 4, and 5, wherein we provide a complex-
ity perspective on what is actually happening within an ecological
system when organizations collide, and why, at times, organiza-
tional life seems so difficult and uncertain. The good news is that
the complexity actually provides tools to make sense of this con-
fusion. Here, we explore the challenges—and rewards—associated
with the nonlinearity of influence among individual human agents
who act within organizations and ecological systems. Chapters 6
and 7 provide ideas, behaviors, and actions to empower individual
human agency within the above complexity. These chapters speak
AQ1
from the individual’s perspective and suggest specific actions that
will enable the thoughtful executive to practice generative leader-
ship and implement the insights in this book. The end of Chapter 7
brings back and again highlights the importance of interaction reso-
nance as a key enabler of the entire process. In Chapter 8 we provide
a summary of the key takeaways that the reader might have iden-
tified throughout the book. We are hopeful that this chapter can
also serve as a refresher, a resource that you can return to again
and again as you develop your skills in the practice of generative
leadership.
We emphasize that generative leadership recognizes the folly of
trying to solve organizational problems through feats of personal
heroism. Instead, complexity science shows how to engage all the
members of an organization through enhanced network connectivity
and interaction resonance. Differences in perspective are encouraged
to coexist and persist since out of them come the seeds of innovation.
This book presents the most significant findings in the field of
complexity science applied to leading the dynamics of innovation.
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INTRODUCTION:ANEW SCIENCE OF LEADERSHIP 17
We discuss how these approaches are already in use in the successes
of Google, Apple Computer, Starbucks, and Merck, as well as many
other entrepreneurial firms and nonprofit organizations. Our hope
is that you’ll find many ways to apply them to your company within
the first week of reading the book. With that in mind, we turn
to Chapter 2, which introduces the fundamentals of ecologies of
innovation.
Notes
1. Chambers, J. T., & Bryant, A. (2009). Openers: Corner office—In a
Near-Death Event, a Corporate Rite of Passage. New York Times. August
2, 2009, p. 2 Business.
2. Hazy, J., Goldstein, J., & Lichtenstein, B. (Eds) (2007). Complex systems
leadership theory. Boston, MA: ICSE Publishing.
3. The term “Generative Leadership” has been used in the past, but more
recently in a complexity context in Surie, G., & Hazy, J. K. (2006).
Generative leadership: Nurturing innovation in complex systems. Emer-
gence: Complexity and Organization, 8(4), 13–26.
4. Gerstner, L. (2003). Who says elephants can’t dance? Leading a great
enterprise through dramatic change. New York: Harper Paperbacks.
5. Ibid., p. 470.
6. Allen, P. (1984). Ecology, thermodynamics, and self-organization.
Canadian Bulletin of Fisheries and Aquatic Sciences, 213: 3–26.
7. Henning, J. (1995). Model Languages: The newsletter discussing newly
imagined words for newly imagined worlds. 1 (4), August 1, 1995.
Available at: http://www.langmaker.com/ml0104.htm#1.