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Original Research
Innovation in a complex environment
Author:
René Pellissier1
Affiliation:
1
Department of Business
Management, University of
South Africa, South Africa
Correspondence to:
René Pellissier
Email:
pellir@unisa.ac.za
Postal address:
PO Box 392, UNISA 0003,
South Africa
Dates:
Received: 27 Aug. 2011
Accepted: 28 Aug. 2012
Published: 28 Nov. 2012
How to cite this article:
Pellissier, R., 2012,
‘Innovation in a complex
environment’, SA Journal of
Information Management
14(1), Art. #499, 14 pages.
http://dx.doi.org/10.4102/
sajim.v14i1.499
Background: As our world becomes more global and competitive yet less predictable, the focus
seems to be increasingly on looking to innovation activities to remain competitive. Although
there is little doubt that a nation’s competitiveness is embedded in its innovativeness, the
complex environment should not be ignored. Complexity is not accounted for in balance sheets
or reported in reports; it becomes entrenched in every activity in the organisation. Innovation
takes many forms and comes in different shapes.
Objectives: The study objectives were, firstly, to establish the determinants for complexity and
how these can be addressed from a design point of view in order to ensure innovation success
and, secondly, to determine how this changes innovation forms and applications.
Method: Two approaches were offered to deal with a complex environment – one allowing for
complexity for organisational innovation and the other introducing reductionism to minimise
complexity. These approaches were examined in a qualitative study involving case studies,
open-ended interviews and content analysis between seven developing economy (South
African) organisations and seven developed economy (US) organisations.
Results: This study presented a proposed framework for (organisational) innovation in a
complex environment versus a framework that minimises complexity. The comparative
organisational analysis demonstrated the importance of initiating organisational innovation
to address internal and external complexity, with the focus being on the leadership actions,
their selected operating models and resultant organisational innovations designs, rather than
on technological innovations.
Conclusion: This study cautioned the preference for technological innovation within
organisations and suggested alternative innovation forms (such as organisational and
management innovation) be used to remain competitive in a complex environment.
Introduction
A complex environment
The modern world has been inundated by catastrophic events that change the business and
social environment and break society’s confidence in stability. In addition, there seems to be
new challenges for the 21st century. Meieran’s (2012) lists of 20th century innovation issues
include: water supplies, the automobile, electricity and air transportation. In contrast, he believes
innovation issues for the 21st century include food and water production, resource protection
and energy conservation. The Center for Strategic and International Studies (2012) identify seven
revolutions for the 21st century, (1) population (growth, aging, migration and urbanisation), (2)
resource management (food, water, energy and climate), (3) technology (computation, robotics,
biotechnology and nanotechnology), (4) information (data growth, access or privacy, education),
(5) economics (global integration, new players, debt, poverty and inequality), (6) security (new
security dynamics, health and cyber security) and (7) governance (civil society and non-profit
organisations, multilaterals and the future outlook).
© 2012. The Authors.
Licensee: AOSIS
OpenJournals. This work
is licensed under the
Creative Commons
Attribution License.
The on-going worldwide financial crisis highlights the sensitivity and interrelatedness of
businesses. It also hints at developing economies being more inclined to accept change in crises
(even to live in uncertainty and instability) than developed economies because of their inherent
capacity to deal with ongoing discontinuous change. Developing economies, especially, are more
prone to the implementation of non-linear solutions because of the nature of the variables, the
changes and interplays between the variables, the significant human foci and the consequent
organic nature of competitiveness. These variables introduce an unavoidable element of
unpredictability or randomness into any science that can be accommodated by a complex
solution. Complexity management allows for pattern recognition which requires focusing on
competencies, activities, technologies or resources signalling patterns that will have a positive or
negative impact on strategy or operations.
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A complex theory possibly provides the only platform
for stability in an otherwise unruly and dynamic world.
Complexity principles could replace the mechanistic ones
based on a well-behaved universe. This article explores the
effect of complexity (external and internal to the organisation)
on organisational innovation and design. In this regard, three
determinant questions should be asked:
1. ‘What are the determinants for complexity in the business
environment?’
2. ‘How can these be addressed from a design point of view
to ensure innovation success?’
3. ‘How will that change innovation forms and applications?’
The research design is qualitative as the research focuses on
emergent phenomena; that is, the emergence of complexity
science in the innovation domain. Interviews were
conducted with a selection of chief executive officers (CEOs)
in developed and developing economies to determine the
extent of organisational innovation in each.
Business as a complex system requires the acknowledgement
that we cannot control organisations to the degree that a
mechanistic perspective will. Moreover, as the system’s
environment changes, so does the behaviour of its agents.
Thus, the behaviour of the system as a whole can change.
Linear strategies and technologies become irrelevant with a
shift to patterns and relationships between entities.
Reasons for organisational
innovation in a complex
environment
Taylorism
Existing management theory is embedded in the four primary
functions: planning, organising, leading and controlling. It
presupposes a linear approach where inputs and outputs
are related and productivity occurs when outputs are bigger
than inputs, in line with Newton’s three laws of motion. In
1911, Scientific Management entered the scene with Taylor’s
four principles (in Fayol 1987), namely, (1) replacing ruleof-thumb work methods with methods based on a scientific
study of the different tasks to be done, (2) scientifically
selecting, training and developing each employee rather than
passively leaving them to train themselves, (3) providing
detailed instruction and supervision of each worker in the
performance of that worker’s discrete task and (4) dividing
work equally between managers and workers, so that the
managers apply scientific management principles to planning
the work and the workers actually perform the tasks. Taylor
insisted that it is only through, (1) enforced standardisation
of methods, (2) enforced adoption of the best implements and
working conditions and (3) enforced cooperation that this
faster work can be assured. He felt that the duty of enforcing
the adoption of standards and enforcing this cooperation
rests with management alone (Fayol 1987). From this
definitive management paradigm more ‘scientific’ control
became the norm enabling the mass-production revolution
to benefit mainly the new elite (e.g. black Ford motor cars
around 1920).
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Original Research
Technology change and a new science
Technology is changing at an unprecedented rate and we
often find ourselves adrift amidst resultant discontinuous
change. There is no luxury of anticipating and planning for
change; rather, as Stephen Hawking (in Porter-O’Grady &
Malloch 2003:36), states, ‘change is’. Instead of being guided
by a set of concrete principles, management in the 21st century
must be fluid and adaptable to keep pace with changing
conditions (Porter-O’Grady & Malloch 2003). In the 20th
century, organisations focused on finding and performing
the right processes; whereas, in the 21st century, the focus
is on delivering the desired outcomes (Porter-O’Grady &
Malloch 2003). The process (or work) itself does not
guarantee that the intended outcome will be achieved. Our
understanding of the future changes on a daily basis and
some would argue that the future is, in fact, unknowable
(Stacey, Griffin & Shaw 2000). In 21st century organisations,
relationships between people inside organisations are the
domain and work of leadership, rather than movement
toward some preselected organisational goal or benchmark.
In order to thrive amidst the unknown, leadership must
embrace new ways of being and interacting (Hamalainen &
Saarinen 2006). These new ways of being, need to be consistent
with the change in the nature of our workplaces. That is,
leadership should be such that it assists to end attachments
to old structures or roles and create new contexts for work
(Porter-O’Grady & Malloch 2003).
Wheatley (1999) laid the groundwork for deeper investigation
into the utility of the new sciences as a way of conceptualising
and understanding leadership in the 21st century. She
focused on, (1) order out of chaos, (2) information forming
and informing us, (3) relationships that enrich and allow for
diversity and (4) a vision as an invisible field that can enable
us to recreate our workplaces and our world. Although
Wheatley’s ideas have been viewed by some as more metaphor
than science (Stacey et al. 2000:143), she made ideas that had
previously been the domain of physicists accessible and
compelling to a much wider audience. Wheatley reflected on
Weick’s (1979:122) observation on the dilemma organisations
face: ‘The environment that the organisation worries about is
put there by the organisation’. Axelrod and Cohen (2000:59)
also provided a comprehensive description of complexity as
applied to organisations, as these authors saw the complexity
science approach as having rich possibilities for bridging the
gap between ‘hard science’ and ‘humanism’. Works such
as Axelrod and Cohen, and Wheatley represent a definite
move away from the mechanistic 20th-century paradigm
of leadership. However, as we start to move away from old
ways of thinking, there seem to be some ideas that are more
difficult to let go of than others.
The living present and a changing conception of
time
From a transformative point of view, the future is under
perpetual construction, rather than predetermined as in
rational causality. This means that human interaction that
takes place in the living present perpetually modifies and
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shapes the future. The concept of time plays a central role in
understanding organisations as complex responses processes
(CRPs) and warrants further discussion. We agree with
Fonseca’s (2002) definition of an organisation as a temporary
stabilisation of themes or habits that serve to organise the
experience of being together that takes place locally and in
the living present.
CRPs represent another decisive step away from the
mechanistic leadership models of the previous century.
Stacey et al. (2000) felt this terminology (i.e. CRPs) was
needed to differentiate their view of complex relational
human organisations from the more commonly used
terminology of complex adaptive systems that leads us to
think of human organisations as objectified systems. The
theory of CRPs is, in essence, a theory of the process of human
interaction (Stacey et al. 2000). A key concept that is essential
in understanding organisations as CRPs, is the idea that
human communication and the act of relating occurs in the
living present (here and now). The living present provides
a starting point for conceptualising causality in a new way.
Rather than thinking of causality in a traditional rational way
(moving toward a mature state or pre-selected goal), focusing
on the living present allows us to conceptualise causality in a
transformative way.
Choice and intentionality arise in, and influence, the microtime structure of the living present. This brings us to the
nature of novelty or change. In transformative causality, the
future is under perpetual construction and is changed by
our movement toward the future: ‘The future is unknowable
but yet recognizable’ (Stacey et al. 2000:52). From a CRP
stance, human interaction is understood as paradoxical and
dialectical (Fonseca 2002; Stacey et al. 2000) and our movement
toward the future is movement toward an unfinished whole
rather than a finished state.
Non-causality and systems thinking
One concept we seem reluctant to let go of is the rational
view of causality. Rationalism frames the organisation as
progressing toward predetermined or preselected goals (the
rise and popularity of strategic planning in the 20th century
is a manifestation of rationalist causality). The rationalist
view of causality is that organisations are moving toward a
future that is preselected by the organisation or toward some
other finished state (Stacey et al. 2000).
Another lingering organisational lens that is used extensively
is systems thinking. Early on, systems were viewed as
machines and, later, we came to use systems thinking as
a way to see organisations as living systems. Either way,
systems thinking has been criticised for having an objectifying
bias (Hamalainen & Saarinen 2006:17); that is, the person
looking at the system necessarily views himself or herself as
external to that system. The ‘detached observer’ is an easy
and comfortable position for most people, as it has been used
in many of the organisational leadership tools developed
in the 20th century. However, organisational life in the 21st
century is highly complex and relational and third-person,
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Original Research
detached views of organisational life fail to address the crux
of leadership today. A new way of seeing and conceptualising
organisations is needed.
Informationology
Modern management has changed with the advent of an
information-based economy. Information has changed
interactions – with each other, with business and between
businesses and entities. With information, there are a
plethora of new meanings and decisions, there is a change
in relationships and there is a change in the very way we
conduct ourselves as individuals, as leaders and managers
and as organisational entities (Pellissier 2001). Some of these
are, (1) relationships and communication, (2) the elasticity of
knowledge, (3) an over-reliance on experts, (4) the trade-off
between richness and reach, (5) a tendency to control and (6)
speed and innovation.
There are many roles of information, some of which may
even overlap (Anderson 1995; Shenk 2009), including:
1. as a complexity (the more information required specifying
a system, the more complex it is)
2. as memory (information is a record of accumulated
knowledge)
3. as communication (information is a means of social
interaction)
4. as intellectual property (information with legally defined
ownership interests)
5. as market enabler (information that permits efficient
markets to function)
6. as context (information regarding the location, time or
environment where the action takes place (Google, in
itself, presents a self-organising system organising around
and following questions asked)
7. as enabler for social interaction (hits are highly visible in
the rapidly growing social networks such as Facebook,
Google+ and Twitter, by establishing links and building
relationships as a ‘re-tribalisation’ of humanity, as
expressed by Shenk [2009:932] when he talks about
strict censorship of Internet connections in repressive
governments).
Growing complexities of resource allocation and
the need for different planning models
The process of planning has to articulate the strategy and
the management of that strategy. From planning comes the
vital means of connecting the mission of the present to the
vision of the future. Part of addressing goals, objectives and
strategy implementation, involves the allocation of resources
within budgetary constraints. This handicaps flexibility by
its focus on cost cutting and efficiencies. Mostly, the budget
defines the plan that defines the strategy.
Peterson (1999) addressed an essential ingredient of strategic
planning – the organisational and environmental interface.
Institutional planning must include a comprehensive process
of monitoring and adjusting for realities of the external
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environment (Taylor, De Lourdes Machado & Peterson 2008).
Complexity encourages a segmentation of the environment.
This allows for the impact of the environmental factors on
resources and resource flows to be examined, which helps
determine resource predictability and the environmental
locus of control with regards to resource flows. The strategic
management and competitive advantage processes become
linear and sequential rather than being seen as one set of
activities, related and linked as one. This kind of planning
relates more to operations than to strategy. Furthermore,
resource allocation is not a linear process and cannot directly
lead to strategy selection and implementation as is required
in a linear model. This planning style does not relate to the
need for adaptability with regards to the environment. The
main goal of the strategic planning and implementation
should focus on growth and maturity and not on internal
processes and resources.
Innovation
Generally speaking, innovation is knowledge used in a
unique and different way. Innovation is new thinking.
That thinking can be radical, disruptive or incrementally
different. But it is not more of the same – it is renewal and
renovation. Innovation is generally the result of cumulative
dynamic interaction and learning processes involving many
stakeholders. Here innovation is seen as a social, spatially
embedded, interactive learning process that cannot be
understood independently of its institutional and cultural
context (Cooke, Heidenreich & Braczyk 2004; Fornaciari
& Dean 1998; Lundvall 1992). Because Roberts’s (1999)
definition (of innovation) maintains that an innovation can
only be seen as innovation if it is has implementation and
commercial value, it is important to measure the impact of
innovation. Ravichandran (2000:263) believe that measuring
the impact of innovation activities will depend on:
1. the typology
2. the degree of departure from the preceding product or
service or process
3. the extent of usefulness of the innovation
4. the volume of profitability generated.
Smith (2010) identifies four types of innovation based on the
work conducted by Henderson and Clark (1990):
• incremental (refining and improving the existing design
within an established architecture)
• modular (use is made of new technology and components,
within an existing system)
• architectural (an established system links existing
components in a new way)
• radical (involving a completely new design using new
components).
In the last case, the innovation can be disruptive. Henderson
and Clark’s (1990) framework shows that systems and
components in innovation are inextricably linked, for
instance, architectural innovation reconfigures an established
system to link existing components in a new way. We like to
define innovation as a continuum of activities incorporating
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Original Research
the above notions: innovation as renovation is the outcome
of a series of interrelated activities on a continuum, starting
with creative discovery, then entrepreneurship and, finally,
commercial exploitation. In this, leadership is redefined,
processes, systems and culture may be redesigned and
organisations search for and find new meaning. This
definition allows for technological (product or process)
innovation but also includes organisational or management
innovation activities.
Innovation within the framework of a knowledge-based
economy goes far beyond the linear or chain linkage models
that have long been used in innovation theory to explain
innovation processes in high-tech knowledge industries.
Strambach (2002) suggests that the interdisciplinary view
of innovation systems is concerned with understanding
the general context of the generation, diffusion, adaptation
and evaluation of new knowledge, which determines
innovativeness. It follows that the focus is on non-technical
forms of innovation as defined above. Common characteristics
of the different approaches to innovation, as identified
by Edquist (1997), include, (1) innovation and learning at
the centre, (2) a holistic and evolutionary perspective and
(3) an emphasis on the role of institutions. The increasing
interdependence of technological and organisational change
is a significant feature of systems of innovation, which
means that technological innovation and organisational
innovation have become increasingly important. These
are combined with more diverse knowledge requirements,
which include not only technical know-how, but also
economic, organisational and sociological knowledge and
competencies. The second reason for the increased interest in
non-technical innovations is associated with the connection
between the organisational innovation and the corresponding
learning capacity. The acceleration of change that is part of
the globalisation process means that organisational learning
processes are becoming increasingly important for creating
and maintaining competitiveness.
Some innovation theorists (such as Smith 2010) believe
innovation is meaningless without technology. Technology
is a great platform for innovation achievement, but it is
certainly not the only one. Technology is a good enabler for
certain types of innovation. But real innovation comes from
the inner self and individual contributions and thoughts
need to be given a place in organisations and in society to
breed. We know that innovation takes place in the domains
of product, process and/or service. However, there is more:
innovation also takes place in leadership, culture, processes
and systems, design, products and technology. Innovation
is a thinking skill more than a doing skill. It transforms
our views of current reality and focuses on renewal and
regeneration. Zohar (1990) believes that:
Most transformation programs satisfy themselves with shifting
the same old furniture about in the same old room. Some seek
to throw some of the furniture away. But real transformation
requires that we design the room itself. Perhaps even blow up
the old room. It requires that we change the thinking behind our
thinking – literally that we learn to rewire our corporate brains.
(p. 114)
However, Zohar’s ‘real transformation’ is really innovation.
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Technological innovation is not
enough
Technological innovation comprises implementing
technologically new products and processes and significant
technological improvements in products and processes. The
product or process should be new from the point of view of the
firm that introduces it. In statistical and innovation research
based on the Oslo Methodology (Organisation for Economic
Co-operation and Development 2005), innovation covers all
possible grades of novelty: from products and processes new
globally (known as absolute innovations), through products
and processes new on a market or in a country, where a
given firm is operating, to products and processes new only
to a given firm, but implemented in other firms, domains
of activity or countries (so-called imitation innovations).
Technological innovation is, in itself, undergoing change
with the shifts in industrial revolution. This is the result of
the evolution of technology. We summarise this as occurring
in three industrial revolutions Firstly, there was the birth
of the factory (e.g. tasks completed by hand in weavers’
cottages are now completed in single cotton mill, leading
to the mechanisation of textile industry), which developed
around the late-18th century in Britain. Secondly, were the
moving assembly line and mass production fostered by
Henry Ford in the early 20th century. Both these revolutions
led to enormous wealth and urbanisation. The third
industrial revolution, on the other hand, is the result of
digital manufacturing and technology convergence – clever
software, new materials, dexterous robots, new printing (e.g.
three-dimensional printing) and Web-based services. This
has resulted in mass customisation and, as a revolution, has
several consequences:
1. customers are happy because of faster lead times and
better products
2. governments providing subsidies favour the previous
products and services in order to protect their investments
3. the lines between manufacturing and services are
becoming blurred.
Technological innovation is created as a result of
innovation activity comprising scientific research, technical,
organisational, financial and market activities in order to
improve a product, process or system. Technical or esthetical
modifications that do not influence the performance,
property, costs, et cetera, are not considered technological
innovations. Generally, we are concerned with process
innovations – ‘performing an activity in a radically
different way’ (Davenport 1993:10), service innovations –
‘a new way of providing a service, often with a novel and
very different business model … even an entirely new
service’ (Smith 2010:23) and product innovations – ‘a core
design concept that performs a well-defined function’
(Abernathy & Clark 1985). Product, process or service
innovations thus comprise both systems and components,
calling for an integrative model for innovation beyond the
instrumentalism versus radicalism approach of the past.
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Organisational innovation encompasses all of these, whilst
highlighting the way businesses operate (Birkinshaw, Hamel
& Mol 2004). These authors maintain that organisational and
management innovation is difficult, as it questions existing
practices and processes and our assumptions on the nature
of the way things are and therefore places an enormous
responsibility on leadership acknowledging complexity
in order to innovate. In this article, we will focus more
on the latter.
Whilst innovation concerns the processes of implementation,
relying mainly on organisational communication and power
in the domains of production, adoption, implementation,
diffusion, or commercialisation of creations (Spence 1994),
creativity remains exclusive to the relation established
between the creator and his product, where not even
originality and usefulness are important, but only the notion
of ‘trying to do better’. The latter is connected to cognitive
and emotional processes taking place at the individual
level (Sousa, Monteiro & Pellissier 2008; Sousa, Pellissier &
Monteiro 2009a, 2009b). If we relate creativity to problem
definition, and innovation to decision implementation, this
last step requires a series of problem definitions, in order to
carry out a decision or an idea, thereby making it difficult
to separate these concepts at an organisational level. In
fact, when we move from the individual level to the team
and organisational levels, creativity and innovation become
increasingly difficult to separate, so that we must agree with
Basadur (1997), when he says there is no difference between
organisational creativity and innovation. Therefore, the
moment we move to other levels besides the individual, we
will use these terms (creativity and innovation) as synonyms,
referring to organisational creativity as a system devoted
to enhance creativity in organisations and thus using the
definition proposed by Basadur (1997).
As to the several approaches to identify types of innovation,
either by separating the adoption of products and processes
from its development (Cebon, Newton & Noble 1999) or,
in a more classical way, product and process innovation
(Adams 2006), most authors agree that innovativeness, or
organisational (and management) innovation, is a separate
type of innovation, which represents the potential of the
workforce to promote changes to benefit of the organisation.
As Huhtala and Parzefall (2007:299) mention, ‘to remain
competitive in the global market, organisations must
continuously develop innovative and high quality products
and services, and renew their way of operating’, and they also
maintain that companies increasingly rely on the employees’
continuous ability to innovate. Also, even though innovation
may take place through the adoption or development of an
existing product or service, through investments in research
and development (R&D) or in technology acquisition, it is only
through developing and sustaining a creative workforce that
the organisation will succeed in maintaining the necessary
potential to overcome difficult problems and situations that
cannot be solved through investments only (Cebon et al. 1999).
To this end, technological innovation is seen as a result of an
innovation activity comprising research (scientific), technical,
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organisational, financial and market activities. Technological
innovation means objective improvement of the properties
of a product or a process or a system of delivery relatively to
the already existing products and processes. Less significant,
technical or aesthetical modification of products and
processes which do not influence the performance, property,
costs or materials consumption, energy consumption and
components consumption are not considered technological
innovations. As Desrochers (2001) puts it, technological
innovation can manifest in any business activity, for example
in a basic activity, as well as in secondary and other activity
(as defined in the system of national accounts), and in the
auxiliary activity of sales department, accounting department,
IT department et cetera (e.g. the computerisation of a sales
department or a finance department of the enterprise can be
considered a technological innovation).
The creative workforce potential is both the ability to retain
creative managers and employees (Macadam 2006) and to
provide an environment where each one will feels free and
willing to contribute to organisational success. Aspects such
as raising job complexity, employee empowerment and
time demands, together with low organisational controls
(decision-making, information flow and reward systems),
are said to raise employee creativity (Adams 2006). However,
more elements are necessary in order to make people willing
and able to contribute to organisational effectiveness. For
instance, supportive leadership, knowledge acquisition
and team work procedures favouring creativity (Unsworth
2005) can add to success. Creative people (either managers
or employees) are committed to their work and organisation
and so they may bring in important issues, provided that top
management values their work and ideas. In fact, according to
a Gallup Management Journal survey (Hartel, Schmidt & Keyes
2003), engaged employees are more likely to ‘think outside of
the box’ and produce creative ideas than disengaged people;
they also are more receptive to new ideas. The research
concludes that engaged people tend to find and suggest
new ways to improve their work and business processes,
which may lead to the assumption that creative people have
a deeper understanding of the organisational processes, by
being in a privileged position to identify, define and find
organisational problems.
To a certain extent, most of these can be achieved by the
implementation of complex systems and the concept of
resilience engineering to the business fundamentals. This
is attained by elevating the importance of creativity and
entrepreneurship and providing a system through which
current goals are realised by new ideas and can flourish.
What is required is the freedom to create, the content and
process skills to be able to create and a supportive human
environment (peers and team leader). The issues surrounding
the potential of an organisation to innovate are still in its
beginnings, although McLean (2005), Puccio et al. (2006) and,
especially, Basadur (1987, 1994, 1997), have all engaged in
empirical research in this regard. The major challenges are
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to define criteria to evaluate the impact of organisational
innovation on process and product innovation (Wolfe 1994).
In organisational innovation, the unit for innovation is the
organisation itself (Wolfe 1994). Although the outcome of the
innovation may be process, product or service, the innovation
needs to be undertaken through the creative inputs of
the individuals and/or management. As to measures of
innovation, Dalal (2008) mentions the qualitative measure of
emotional and psychological impact the innovation produces
on the users (the ‘aha!’ moments), the quantitative measures
of the total population of end users using the new innovation
(and even helping co-create it) and the net new revenue
generated for the company that can be attributed to the new
innovation.
Complexity-based emergent
management theory
Complexity allows a two-tiered focus in business, (1) its
performance system, which is responsible for the performance
of current goals and tasks for immediate survival and (2)
its adaptation system, which is responsible for the longterm sustainability through the generation of new ideas,
operations and behaviours. It generates possible futures for
the total systems. Successful resilient organisations should be
robust in terms of both subsystems but tend to concentrate
on only one (Robb 2000). The term ‘complexity’ has two
distinct applications (Standish 2008), namely, (1) as a quality
(i.e. complexity deals with our ability to understand a system
or object) and (2) as a quantity (i.e. complexity deals with
something being more than complicated). Complexity as a
quality is what makes the systems complex and complexity as
a quantity describes, for example, human beings being more
complex than a nematode worm. Thus, complex systems
constitute a class of systems that are more difficult to deal
with than traditional analytical systems. For this reason,
complex and simple systems form a continuum, characterised
by the chosen complexity measure. The two applications of
complexity are inherently observer or context dependent,
leading to a disparate collection of formalisations of the
term. Thus, being able to establish easy to measure proxies
for complexity is often important and most proposals for
complexity are of this nature (Standish 2008:10). Complexity
as a quantity can normally be decomposed in a linear way and
can be directly compared (e.g. 5 cm can be broken into five
equal parts and directly compared). Complex systems, on the
other hand, cannot be divided and the individual segments
compared. This is because of the interrelations between the
subsystems that can quickly lead to combinatorial explosions.
This leads to three definitions of complexity (Standish 2008).
Firstly, there is the number of parts definition (e.g. a car is
more complex than a bicycle because it has more parts,
but a pile of sand is not as complex because each grain of
sand is conceptually the same and the order of the grains is
not important). Secondly, there is the definition relating to
the number of distinct parts (e.g. both a shopping list and
a Shakespearean play consists of the same 26 letters of the
alphabet, this is not a good measure of complexity). Lastly,
there is a context-dependent definition of complexity.
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When we relate business to complex adaptive systems (CAS)
– also called learning systems (Robb 2000) – we look for ways
to successfully adapt to changing environmental conditions.
Complexity science focuses on relationships between
individuals, teams or between organisations and businesses.
Accepting business as being a complex system requires that
we acknowledge that we cannot control organisations to the
degree that a mechanistic perspective will imply, but only that
we can influence where the organisation is going and how
it will evolve. From this view, organisations are CAS nested
in larger CAS (for instance, the economy or the country in
which it is based, or the industry in which it operates). Lastly,
complexity science allows an organic view of organisations
and its resources. Resilient organisational structures, in
focusing on the skills, culture and architecture, address this
matter and will be discussed in a separate section.
Simon (1996) defines a complex system as one made up
of a large number of parts that have many interactions.
Complex systems change inputs to outputs in a non-linear
way because the components interact with each other
through a web of feedback loops (Anderson 1999a:217).
Thompson and MacMillan (2010:6) describe a complex
organisation as a set of interdependent parts which, together,
make up a whole that is interdependent with some larger
environment. In organisation theory, complexity is treated
as a structural variable that characterises both organisations
and their environments. In terms of the first mentioned, Daft
(1992:15) equates complexity with the number of activities or
subsystems within the organisation. This, he maintains, can
be measured along three dimensions, namely, (1) vertical
complexity (the number of levels in the organisational
hierarchy), (2) horizontal complexity (the number of job
titles or departments across the organisation and (3) spatial
complexity (the number of geographical locations. With
regards to the environment, complexity is equated with the
number of different items or elements that must be dealt
with simultaneously (Scott et al. 1998:230). Galbraith (1982)
proposes that organisational design should try to match the
complexity in structure to complexity in environment. Casti
(1994) points out that, in non-linear systems, interventions
to make a change to one or two parameters can drastically
change the behaviour of the whole system. Moreover, the
whole can be very different from the sum of the parts.
CAS consists of agents that interact with each other and, in
doing so, generate new behaviours for the systems as a whole
(Lewin & Regine 1999). These lead to the following caveats:
• Patterns of behaviour in these systems are not constant.
• As the system’s environment changes, so does the
behaviour of its agents. Thus, the behaviour of the system
as a whole can change.
• Complexity science focuses on relationships between
individuals, teams or between organisations and
businesses.
• Business as a complex system requires acknowledgement
that we cannot control organisations to the degree that a
mechanistic perspective will.
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• CAS allow for an organic perspective and the ability to
deal with the human element in process design.
Complex designs are formulated to attend to the tensions
of paradoxical strategies which may emanate from
inconsistencies or contradictions in the products, services,
marketplace, processes, rewards and/or competencies
associated with different strategies (Smith 2010). Considerable
attention has been given to agent-based models of organic
systems (McKelvey 1999). In modelling complex systems, we
should note that agent-based models need to avoid adoption
of social concepts that assume away many of the phenomena
of interest. In fact, McKelvey (1999) argues, if at least some
social phenomena, which are typically assumed to arise
through rational behaviour, arise instead because of complex
dynamics that are little influenced by conscious intent, then
we need to allow for this in the foundation assumptions
incorporated into the model design. In artificial intelligence,
for instance, attempts to accommodate rational order have
involved incorporating simplified rule sets or incorporation
into agent design.
Linking complexity and innovation
What do these two phenomena have to do with each other?
Complexity science is the scientific study of complex systems.
These systems have many parts that interact to produce
patterns of behaviour that cannot readily be explained by the
behaviour of its individual elements. Therefore complexity
in business helps us better understand the importance
of relationships and the interactions of innovations.
Complexity science is used in modern business applications
because of its ability to explain change and stability and the
underlying dynamics produced by patterns in systems and,
most importantly, self-organisation and emergence. This
means that individual agents in a system cannot control
the behaviour or the outcomes of the system because these
agents are the consequences of interactions within the system
and with other systems. Consequently, complex systems
are, by nature, unpredictable and can lead to renewal and
change (radical or otherwise). This makes complexity science
invaluable to innovation. From an innovation point of view,
this means that the best way to understand the dynamics of
change and innovation is to employ complexity science.
Yet, complexity science does more than that – it allows
for diversity, relationships and cooperation. Complexity
science changes how management works. The inherent
self-organisation and unpredictability mean that there is
less control. Leadership thus requires change as there is
less control and more focus on small actions to influence
patterns of interaction. Smaller organisations are, of course,
more flexible and thus more able to be innovative. Thus,
the size of the organisation counts because it is easier to
develop relationships and creativity in a smaller group
and there may be a greater willingness to release control.
Larger organisations seem to become inflexible and rulebound. Their flexibility is normally embedded in specific
units, but overall, there is a notion that adaptive and resilient
systems are characterised by order or disorder, or stability or
flexibility. In a complex environment, there is no ‘either/or’.
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To apply complexity to innovation, one needs certain
principles. Zimmerman, Lindberg and Plsek (2012) suggest
the following:
• The provision of opportunities for a diverse group of
people to interact creatively.
• The design of processes to develop creativity, for example,
appreciative enquiry, open space, conversation cafes.
• The adoption of a shorter-term perspective stimulating
experimentation and sense-making of the ideas, instead of
developing a grand plan or long-term blue print.
• The management of innovation should be centralised (to
develop an innovation culture organisation-wide) and
decentralised (encouraging experimentation at the local
level). This is the principle of non-linearity, where the
strategy allows small changes effecting large-scale change.
• Leadership should have the ability to listen to promising
developments, create network opportunities and
communications across the organisation and allow for
pattern recognition and new innovations to unfold.
Complexity science requires a change in leadership to
support the innovation. This new leadership should:
• Create a culture of innovation. Leadership cannot make
innovation happen, but they foster innovation by providing
the time and space for creativity, communication and
interaction.
• Listen and learn to determine what is emerging in the
organisation or in its environment.
• Learn by taking risks and allowing experimentation in the
form of ideas or processes.
Two frameworks in this regard are proposed below.
Framework 1 employs complexity and CAS in innovation,
whilst framework 2 uses a reductionist approach seeing
complexity as something negative to the organisation.
Framework 1: Using complex adaptive systems
Rosen (1991) founded the school of thought which believes
that complex systems cannot be described by a single best
model, as reductionists promote. Instead, a whole collection
of models exist that, in the limit, collectively describe the
system. Standish (2008:9) mentions that in all cases of
recognised emergence, the observer has defined at least one
semantic and one syntactic model of the system; these models
are ‘fundamentally incommensurate’. Moreover, emergence
in this sense can be called complex. Models that have a finite
specification can never be complex, because the specification
contains all there is to know about the system – the more
complex the system, the less knowable the organisation is
(Perrow 1967); however, it is not so easy with non-linear
systems. Obviously, causal models are inadequate because
of their interconnectedness and feedback loops, even when
the relationships between the independent and dependent
variables are denoted by some logarithmic or exponential
function. There are six important aspects to be considered
in modelling complex systems (Anderson 1999b;
Kaufman 1993):
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• Many dynamic systems do not reach either a fixed-point
or a cyclical equilibrium.
• Processes that appear to be random may be chaotic,
revolving around identifiable attractors deterministically
and rarely return to the same state.
• The behaviour of complex processes can be quite sensitive
to small differences in initial conditions, so that two
entities with similar initial states can follow radically
different paths over time.
• Complex systems resist simple reductionist analyses
because their interconnectedness and feedback loops
preclude holding some system constant in order to study
others in isolation. Because descriptions at multiple scales
are necessary to identify how emergent properties are
produced, reductionism and holism are complementary
strategies in analysing such systems.
• Complex patterns can arise from the interaction of agents
that follow relatively simple rules; that is, emergent
patterns can appear at every level in a hierarchy.
• Complex systems tend to exhibit self-organising
behaviour; that is, from starting in a random state, they
usually evolve toward order instead of disorder.
There are many forms of dynamic systems, for example,
general systems theory, cybernetics, chaos theory or
catastrophe theory – all of which address systems where a set
of equations determine how a system moves through its state
space over time. Another modelling technique examines
regularity that emerges from the interaction of individuals
connected in CAS. The presiding feature is that at any level
of analysis, order is an emergent property of individual
interactions at a lower level of aggregation. Anderson
(1999b), in his study of complex organisations, found that
these organisations exhibit non-linear behaviours. He found
that these organisations characterise four key elements that
are prevalent in organisation design, namely:
1.
2.
3.
4.
agents with schemata
self-organising networks sustained by importing energy
co-evolution to the edge of chaos
system evolution based on recombination.
It follows that organisational designs for complexity will
require incorporation of these elements. Specifically,
complex organisations establish and modify environments
within which effective, improvised self-organised solutions
can evolve and managers influence strategic behaviour
by altering the fitness and landscape for local agents and
reconfiguring the organisational architecture within which
the agents adapt. Lewin and Regine (1999) identify five
principles in CAS:
• Agents interact and mutually affect each other in a system
– this focuses on relationships between and amongst
people, teams and companies.
• Agents’ behaviours in a system are governed by a few
simple rules – in business, rules become practices and
these practices are guided by shared values and beliefs.
• Small changes can lead to large effects, taking the system
to a new attractor – multiple experimentation on a small
scale is the most productive way to lead change rather
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than to attempt to leap too quickly to a perceived desired
goal on a large scale.
• Emergence is certain, but there is no certainty as to what
it will be – create conditions for constructive emergence
rather than trying to plan a strategic goal in detail. This
includes nurturing the formation of teams and creativity
within teams and evolving solutions to problems (not
designing them). Hierarchical and central control should
give way to distributed influence and a flat organisational
structure.
• The greater the diversity of agents in a system, the richer
the emergent patterns – seek diversity of people in terms
of culture, expertise, age, personalities and gender, so that
people interact in teams (thus creativity has the potential
to be enhanced).
A substantive element of complexity in organisational
designs is made up of organisational resilience. Robb
(2000) defines a resilient organisation as one able to
sustain competitive advantage through its capability to
deliver excellent performance against current goals, whilst
effectively innovating and adapting to rapid, turbulent
changes in the environment. The first requires consistency,
efficiency, elimination of waste and maximising short-term
results, whilst the second requires foresight, innovation,
experimentation and improvisation, with an eye on longterm benefits (Johnson-Lenz 2009). The two modes require
different skills sets and organisational designs (e.g. the move
from ‘just-in-time’ production to ‘just-in-case’ resilience).
These organisations exhibit particular characteristics in the
sense that they, (1) can create structure and dissolve it, (2)
provide safety in the face of change (although this is not
necessarily security or stability), (3) manage the emotional
consequences of continuous transformation, change, anxiety
and grief and (4) learn, develop and grow. The resilience
community agrees that resilience architecting (also called
resilience engineering) occurs over the three phases of a
disruption. In the pre-disruption phase, the system should
take steps to anticipate the disruption and avoid the
disruption, if possible. In the survival phase, the system
should absorb the disruption so that it can recover in the
recovery phase. In the recovery phase, the system resumes
some degree of its original goals, including the survival of
the humans in it. Disruptions are the initiating event that
may lead to a catastrophic event. Disruptions may be either
external, such as terrorist attacks or natural disasters, or
internal, such as human or software errors.
Resilience has four primary attributes: capacity, flexibility,
tolerance, and inter-element collaboration. Capacity requires
that the system be sized to handle the maximum and most
likely events, such as terrorist attacks and natural disasters.
However, a system cannot depend on capacity alone; the
other attributes must be present to handle unpredicted
events. Capacity includes functional redundancy. Flexibility
requires the system to be able to reorganise. For example,
plans must be in place to allow the command and control
to shift upwards in the event of a serious disruption, such
as a terrorist attack. Tolerance allows the system to degrade
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gracefully in the face of an attack; that is, all resources would
not become inoperative after the first strike.
One of the most important resilience attributes is inter-element
collaboration. This attribute allows all elements of the system
to interact and cooperate with each other as in collaborative
innovation systems. There are numerous activities relating to
resilient organisations, these are (Pellissier 2011:156):
• Resilient organisations actively attend to their
environments: Monitoring internal and external indicators
of change is a means of identifying disruptions in advance.
Resilient organisations seek out potentially disturbing
information and test it against current assumptions and
mental models. They work to detect the unexpected so
they can respond quickly enough to exploit opportunity
or prevent irreversible damage. In short, they anticipate
being prepared.
• Resilient organisations prepare themselves and their
employees for disruptions: Attentive preparations
build a team that imagines possibilities and displays
inventiveness in solving problems. Managers know how
and when to allow employees to manage them for focused
productivity as well as adaptive innovation. Resilient
organisations cross-train employees in multiple skills
and functions. They know that when people are under
pressure, they tend to revert to their most habitual ways
of responding.
• Resilient organisations build in flexibility: Even whilst
executing for lean and mean performance, resilient
organisations build in cushions against disruptions. The
most obvious approach is the development of redundant
systems – backup capacity, larger inventories, higher
staffing levels, financial reserves, and the like. But those
are costly and not always efficient. Flexibility is a better
approach.
• Resilient organisations engage suppliers and their
networks in devising makeshift solutions to temporary
disruptions, thereby using flexible strategies: They
implement policies that encourage flexibility in when
and where work is undertaken. Employees who are used
to telework and virtual workspaces adapt more quickly
and are more productive following a crisis. In addition,
research shows that flexible work practices contribute to
greater employee resilience, productivity, commitment
and to lower levels of stress.
• Resilient organisations strengthen and extend their
communications networks – internally and externally:
A robust and redundant communications infrastructure
holds up in a crisis. Social networks amongst employees at
resilient organisations are rich, varied and visible. People
who have trust relationships and personal support systems
at work and with friends and family are much more able
to cope with stress and change. Good connections and
communications also apply to external relationships with
suppliers and customers. A key is to recognise what is
important to meet organisational goals and to listen to
those with needed expertise and ideas wherever they are
in the value web. Resilient organisations use networked
communications to distribute decision-making. As much
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as possible, they push decisions down to where they can
be made most effectively and thus quickly. This, in turn,
requires good access to information at all levels of the
organisation.
• Resilient organisations encourage innovation and
experimentation: In times of great uncertainty and
unpredictability, the success and failure of small-scale
experiments can help map a path to the future. Resilient
organisations engage in market research, product
development, and ongoing operations and service
improvements. They invest in small experiments and
product trials that carry low costs of failure.
• Resilient organisations foster a culture of continuous
innovation and ingenuity to solve problems and adapt
to challenges: A side benefit is that employees who
believe they can influence events that affect their work
and lives are more likely to be engaged, committed, and
act in positive ways associated with resilience. Some
organisations also have internal idea markets to surface
new ideas and innovations. Others use ‘crowdsourcing’ to
engage people externally in solving a given problem.
• Resilient organisations cultivate a culture with clearly
shared purpose and values: When an organisation’s
sense of purpose is shared by its employees, suppliers
and customers, those networks can provide flexibility to
help it through a disruption. Engaged employees will seek
out opportunities to try new approaches, find creative
solutions and achieve great results.
Framework 2: Complexity reduction
The second framework tries to reduce complexity and sees
complexity as negative towards the organisation. It is not
easy to compress non-linear systems into a parsimonious
description. Simon (1996:1) believes that the central task
of the natural sciences is to show that complexity is but a
mask for simplicity. In the Social and Management Sciences,
the tendency seems to be to reduce complex systems to
simpler ones by abstracting out what is unnecessary or
not important. Most organisational scientists, who view
organisations as natural systems, point out that rules often
do not govern actions and that rules can change without
behavioural consequences and behaviour can change without
modifications to rule systems (Scott 1992).
Normally, competitive advantage is about new product
development and the introduction of distinctive offerings. In
fact, technological innovation seems to be the most prevalent
form of innovation. There is a school of scientists that believe
that the longer an organisation has been in existence, the less
likely it will allow for radical innovation (Anderson 1999a).
The literature abounds with case studies about innovators
and entrepreneurs who make things happen. However,
there is a point where the innovation leads to a decrease in
profitability because of the complexity that it incurs. The
continued launch of new products and services or changes
in design or movement styles lead to complexity. This is
supported by a survey conducted by Bain Consulting (2012),
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which found that excessive complexity increases costs and
slows growth because of the way complexity gets embedded
in the supply chain. The corporate response seems to be
to launch an intervention (such as lean manufacturing or
six sigma). This, however, does not simplify complexity;
it merely reduces it in certain areas. There are numerous
reasons for the spread of complexity: bad economic data,
overly optimistic sales expectations, entrenched managerial
assumptions and, in developing economies: globalisation,
labour problems, customisation versus market size one,
new technologies, political instability, lack of infrastructure,
resources and capacity, and lack of planning. Bain Consulting
(2012) believes that downturns reveal organisational
weaknesses and that a nimble, focused organisation could
become ‘sluggish and ineffectual’ in a period of downturn.
They see a major cause of this sluggishness as complexityproduct complexity, organisational complexity and process
complexity. The costs of complexity are usually hidden, so
CEOs are often unaware of the magnitude of the problem.
When the downturn hits, CEOs may feel unsure how to
tackle it or fail to identify the short-term actions that can
reduce costs and create flexibility so the company can
adjust to the new market conditions. They may also neglect
the longer-term steps necessary to balance complexity
reduction with innovation as the company pulls out of the
downturn and begins to grow consequently – there needs to
be a balance between innovation and complexity. Consider
manufacturing, which is a strong American economic enabler.
From a strategic point of view, the addition of new products
increases growth. From an operational point of view, this
addition adds complexity and thus decreases profitability.
Moreover, increased customisation results in unexpected
demand peaks that can easily lead to a drop in quality. The
traditional financial systems are unable to account for the
relationship between product proliferation and complexity
costs, as the costs are embedded in the way the organisation
undertakes its business. There seems to be an optimum point
for innovation, unless there is a management of the resultant
complexity (Gottfredson & Aspinall 2006).
Some protagonists believe in reduction to diffuse complexity.
For instance, Gottfredson and Aspinall (2006) proposed a
‘Finding the model T Ford’ approach. The approach is based
on determining the innovation ‘fulcrum’; that is, determining
the right balance between innovation and complexity. The
following practices are required:
1. Raise the bar: requiring a higher rate of return on new
products not only makes it more difficult to arbitrarily add
variations, it also boosts internal innovation discipline.
2. Postpone complexity: the farther down the value chain
complexity is introduced, the less it costs.
3. Institutionalise simplicity in decision-making: executives
must pinpoint responsibility for innovation decisions.
4. Stay balanced: a company’s innovation fulcrum can shift.
Sometimes customers value cost and quality more than
having choices.
Technology, postponing complexity to later in the value
chain and changing customer tastes can all affect where the
right fulcrum point is located.
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A comparison between developed
and developing organisations
In a study of 14 mid-sized organisations from either a
developed or a developing economy, the respective CEOs
were interviewed. The purpose of the study was not to
generalise but functioned as a pilot study to determine issues
of complexity and organisational innovation between the
two economic entities. Seven middle-sized South African
companies were selected as the developing economy partner
and seven middle-sized US companies were selected as
the developed economy partner. The CEOs of each were
asked to describe their understanding and deployment of
organisational innovation and complexity. They were also
given a set of complexity and organisational design issues
and asked to comment about the extent to which their
companies were exposed to these and how they perceived
the solutions. The interviews focused on the extent of their
organisational innovation and their understanding and
implementation of complexity to achieve the innovation.
Below is a sample of responses from four of the companies
involved in the study.
Company A
This is a medium-sized US firm specialising in health and
education research and operating out of several cities
in the USA. According to the CEO, larger, more nimble
firms had better systems to enable them success, whilst,
in Company A, there was an over-focusing on quality and
accreditation of research outputs rather than on market
position and competition. Two primary problems existed: an
over-emphasis on research quality and an under-emphasis
on efficiencies, both of which lead to budget constraints.
Operational problems included inefficiencies and lack of
structure. This company’s strategy seems to rely on a reengineering approach in terms of the following elements:
1.
2.
3.
4.
5.
6.
appointment of senior research specialists
building teams
creation of management systems and accountability
change in culture
becoming client-focused
specialising on something specific.
Their strategy is certainly linear – in the CEO’s own words,
it is aimed at ‘putting the firm on a straight path and staying
on that path’. He also maintains that:
‘A linear strategy was required because of the competitive nature
and scale of the environment and a required change in one
direction. We are not in a tumultuous environment and had to
adapt to the new path and merely be able to stay on that path.’
(CEO, Company A)
Evaluation of Company A’s strategy
The CEO did acknowledge that there were two conflicting
objectives – making money and being efficient – which may
have required a complex solution, but, he felt that, as long
as they stayed in the new path, they should be successful.
The CEO did not understand the role or value of adaption,
resilience or agility.
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Company B
This is a medium-sized bank in the USA. When the current
president of the bank took over, there was little wrong
with the strategic direction; however, there was no vision,
only the mission. The new president decided not to select
objectives but identified three key priorities that inform their
strategy and remain constant, (1) fiscal soundness, (2) focus
on customers and (3) focus on the community. Believing
that management has changed substantially over the last 20
years, the president practices the following with regards to
strategy, which includes the following principles:
1. strategy is about common sense
2. strategy is a journey not a destination, with the journey
indicating the general direction
3. it is important to track who you are
4. you need to communicate that you are a real person.
Further to this last point, the bank president states, ‘Don’t
sit up there, go down to the people and ask them what they
would do if they were president.’ The elements of Company
B’s strategy were, (1) a flat organisational structure, (2) the use
of teambuilding exercises and (3) a collaborative approach to
management.
Evaluation of Company B’s strategy
Employees felt confident enough to discuss issues inside the
discussion room and not amongst themselves in the corridors,
rather than resorting to complaints outside the discussion
room. Company B featured a smaller management team and
was subject to less interference from the Board. Although its
structure was now flexible, some employees did not agree
with the new approach and left the bank, thereby providing
a natural exit for employees in disagreement with the general
flow of the strategy and its implementation. Thus, there is
stability within the unstable environment.
Company C
This is a medium-sized risk management venture in South
Africa. The CEO, who, at the time of this survey, had
been appointed for one year, sees his role as ‘never lonely,
participative and directive, experiential and experienced
participative’. Their strategy consists of the following
elements:
1. strategic management is very important, although flexible
2. strategy is monitored as a journey as often as twice a week
3. there are no ‘analogue activities’, only ‘acting and thinking
digitally’
4. engaging in strategic planning is a continuous process
using the concept of a sense-making loop from uncertainty
to a shared understanding
5. their intent is to manage future risks before they take place
6. the execution of their strategy employs action learning,
experiential learning and serious play are the methodology
framework for the planning sessions
7. a talent analysis, learning and communication styles
linking assignments to a group of various competencies.
Teams change depending on the task.
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Evaluation of Company C’s strategy
Strategy in Company C happens as continuous loops, rather
than as a planned exercise. This strategy is very flexible and
teams are formed based on a specific need. There is a feeling
of openness and conviviality amongst the employees and the
CEO is seen as friend and not as executive.
Company D
This is a medium-sized (family-owned) manufacturing
organisation in South Africa, which also exports to other
countries. In regards to how he views his role within the
organisation, their CEO writes:
‘At times I play the classic ‘lonely’ CEO, off by myself thinking
and dreaming of what could/should be within the organisation.
Creative inspiration or concrete decision may come at any time
including during the wee hours, driving my daughters to school
or while having lunch. I am participative during many “blue
sky” meetings, where my role is decisive in theory but I am just
another voice for the most part.’ (CEO, Company D)
Strategy and innovation are seen to be linked and to provide
the overarching framework for their daily actions, but putting
too much emphasis on the process can choke the organics out
of running an organisation. The CEO does believe in nonlinearity and will:
‘Literally talk to everyone and anyone in the organisation on
an hourly basis. I never assume that I have all the answers and
many times the best ideas and concepts will arise from a chance
encounter with a staff person. So I don’t leave those encounters
to “chance” – I create them often.’ (CEO, Company D)
They are constantly re-evaluating their vision, mission, values
and strategy using a process that includes regular meetings
with top and middle management and by carefully listening
to line-level employees and customers every day. Their main
goals are to achieve a strong position in the industry-related
marketplace, maintain a very high level of product quality
and make their business a fun and interesting place to work
and to turn a profit in doing so.
Evaluation of Company D’s strategy
Company D’s strategy is linear, with traces of non-linearity.
Their strategies include marketplace analysis, competitive
analysis and informal SWOT (strengths, weaknesses,
opportunities and threats) analysis. Their strategy has
changed from a ‘shoot from the hip’ organisation to one more
analytical, reviewing numbers carefully.
Discussion
There can be no generalisation because of the small, nonprobabilistic sampling. However, some degree of relative
comparison can be made and the pilot study sets the stage
for a more robust study across the two economies to follow.
From the interviews, a number of points came to light,
including that more South African organisations were, by
nature, complex, whilst more US organisations were, by
design, linear, despite being inherently complex. The US
companies were not comfortable with the CAS model and
endeavoured to use some form of reductionism to achieve
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results when faced with complexity. Also, the US companies
were more involved in experimental products, strategic
alliances, meetings, communication with customers,
communication within projects, but less so in teambuilding,
exploitation (refining and extending existing technologies)
and exploration (searching and experimenting with new
technologies). In fact, it seems that South African companies
are managed using complexity techniques and all innovation
forms by nature, whilst the US ones favoured a reductionist
approach focusing on technological innovation and trying to
simplify structures and processes.
Technology was favoured by both groups as the factor most
considered in a complex environment. As was expected,
the US companies did not experience the developing
economy indicators (problems with labour, productivity,
clashing cultures, training and development, understanding
and implementing new technologies, geographical
dispersion, communication or quality). The South African
companies had problems with: value and supply chains,
new innovations, inadequate knowledge management
and business intelligence, low capacity utilisation, no link
between people and process, performance criteria and badly
articulated connections between business units. On the other
hand, the South African companies were more involved
in exploiting and exploring opportunities and thus could
be classified as engaging in the complexity suggested in
Framework 1. Although this is not conclusive evidence, there
seems to be adversity (even rigidity) in the US companies to
explore forms of complexity and innovation other than, at
most, technological innovation, and a feeling of comfort in
reducing complexity, as per the proposed Framework 2.
Conclusion
Complexity is neither complicatedness nor overdetermination. Complexity is a cross-disciplinary field with
its own approach to knowledge-creation that includes a set
of methodological approaches. As such, it offers distinct and
innovative perspectives on the evolution of systems and the
behaviours of the actors within them. And, it should be noted
that complexity, in itself, is not an ‘either/or’ to traditional
management models. Instead, it expands and augments
these models. Complexity theory is particularly relevant
for organisations facing rates of external change that exceed
their internal change (McKelvey 1999). Unlike systems with
a fixed-point or cyclical equilibrium, the instability in the
global environment has a more dynamic equilibrium in
which actions can lead to small, medium or large cascades
of adjustment.
Brown and Eisenhardt (1998) suggest that single business units
achieve rapid evolutionary progress through improvisational
moves based upon a few simple rules, responsibilities, goals
and measures. These authors offer a new strategic paradigm
for navigating the tumultuous markets:
the key strategic challenge facing managers in many
contemporary businesses is managing this change. The challenge
is to react quickly, anticipate when possible, and lead change
doi:10.4102/sajim.v14i1.499
Page 13 of 14
where appropriate. A manager’s dilemma is how to do this, not
just once or every now and then, but consistently. (p. 23)
Synergy amongst units follows when units have distinct roles
participating in the larger focus. Collaboration is focused
on a few key areas. Evolution is preferred over the radical
revolution preached and implemented by the re-engineers of
the 1990s.
We agree that a nation’s competitiveness lies in its
innovativeness. Innovation is a dangerous beast that bodes
evil and destruction when used inconsiderately because
of the changes and possible aggravated complexity it
incurs. This makes innovation management critical. It also
requires a deep understanding of the nature and forms of
innovation and a willingness to create opportunities for
creativity. Technological innovation is not necessarily the
best innovation. However, with an increasingly complex
environment and complexity within the organisation
following on innovations, organisational innovation seems
required. In this research, a comparison was made between
developed and developing economies with regards to how
companies handle their innovations whilst coping with
complexity. There is reason to believe that developing
economies are more able to handle the extent of complexity
than their developed counterparts.
This research is by no means final or complete. The pilot study
should be extended to a bigger sample from both economies.
Questions that need to be addressed include, (1) the extent
to which complexity hinders or support innovation, (2) new
typologies for innovation within a complex environment
and (3) a point of convergence between developed and
developing economies – when and why?
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The author declares that she has no financial or personal
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