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6. Forelæsning – d. 7. oktober 2013 Strategisk ledelse

Lectures, autumn 2013

Cognitivist and humanistic psychologySender-Receiver model • Initially, the human brain was thought of as a deductive computer, performing logic operations • Intelligence was equaled with computation, so cognition (human knowing) could be understood as a process of computing representations of reality • Learning is when the pre-given reality is more and more accurate represented by negative feed-back • Emphasis on internal representation of external environment and learning by negative feed-back • Sender-Receiver model of communications • The human mind becomes one of the variables that can be designed and changed as cybernetic systems

Cognitivist and humanistic psychologyHumanistic psychology Takes an optimistic view on human nature Alienation of the true self because of revivalism Focus on human motivation, values, beliefs and the importance of leadership vs. rational decisions Sharing culture and formulating a common vision, which still is at the core of cybernetics theory

Cognitivist and humanistic psychologyHumanistic psychology - motivation

Cognitivist and humanistic psychologyHumanistic psychology Mission statements (believing in what is being done) captures emotional support from employees and thereby paves the way for motivated employees Vision: picture of future state Mission: a way of behaving Organizations will be successful when people are emotionally engaged and inspired by visions and a sense of a mission and it is the role of leaders to choose these

Cognitivist and humanistic psychologyLeadership / Groups Leader translates higher level directives to goals and tasks for his/her part of the organization, monitors performance and ensures motivated employees Two basic leader styles; autocratic / delegating Leadership style applied is context dependant Formal groups requires psychological awareness, clear goals, tasks and their purpose is to solve problems Informal groups may develop, primarily driven by physical proximity and not hierarchal relation Such informal groups may jeopardize motivation, control systems and other formal structures

Strategic Choice Theory Key questions: Strategy determines structure or vice versa? Market position or resource base determines competitive advantage? Limits to strategic choice, particular when it comes to uncertainty and the impact of cognitive frames in interpreting situations. Process versus content leading to an emphasis on learning rather than simple choice

Complexity Sciences

The complexity sciences Strategic Choice Theory Complex Responsive Processes Transition All ideas in section 1 (chapter 1-9) is imported from natural sciences and complexity theories could present significant challenges to this way of thinking The complexity sciences will establish the transition from section 1 to section 3 of the textbook

Chaos theory Chaos theory is not to be regarded as utter confusion! It is an extension of systems dynamics and focuses on the phenomenon is changing over time The model is iterated over time, which means that calculated output of one period is taken as input for the next calculation and identifies dynamical properties In system dynamics, a model can, at one point, display an equilibrium. In chaos theory, the ‘Point Attractor’ settles for such an equilibrium. At other points, the model displays perfectly stable and predictable cycles of movement which is referred to as ‘Cyclical’ or ‘Period two, attractor’

Chaos theory The highly unstable behavior, for certain parameter values, of system dynamics is referred to as ‘high-dimensional chaos’ – a pattern of fragmentation Between stable parameter values (point or cyclical) and unstable values (chaos) the system moves in a manner that seems random, but displays a pattern The pattern is regular irregularity or stable instability which means it is predictably unpredictable Paradoxical pattern of movement; Strange attractor, which is referred to as Mathematical Chaos and is a completely differently dynamic where stability and instability is inextricably intertwined

Chaos theory High sensitivity to initial conditions and even tiny differences in the input of one period can escalate so that patterns change qualitatively in later periods Long-term predictions is therefore impossible! Weather systems actually follows a Strange Attractor and can be visualized as the ‘Butterfly Effect’ Short-term predictions are possible, because it takes time for tiny differences to escalate Impossible to identify specific causes the produces specific outcomes, but boundaries and the nature of the patterns are known

Chaos theory Chaos theories do not have the internal capacity to move spontaneously moves from attractor to another, this requires an external force for parameter change Causality continues to be formative and chaos models are unfolding the pattern already enfolded in its mathematical specification Incapable of spontaneously generating novelty

Dissipative Structures Based on demonstrations that shows how physical and chemical systems displays unpredictable forms of behavior when far from equilibrium Systems may reach critical points where they self-organize to produce a different structure or behavior that cannot be predicted from knowledge of the previous state This more complex structure is called Dissipative Structures because it takes energy to sustain that new mode

Dissipative Structures • Example with thermodynamics • Closed to environment and temperature uniform • At a state of rest on global level (no bulk movements) • Movements of molecules are random and independent • System behavior is symmetrical, uniform and regular • When heat is applied, the liquid is pushed far from its equilibrium and small fluctuations are amplified throughout the liquid • Temperature change at the base is amplified or spread through the liquid. Molecules start to move upward • Established convection so molecules least affected are displaced and moved down to the base • The molecules are now moving in a circle • At a certain temperature point, the molecules start setting up hexagonal cells and turning both ways • The cells are self-organizing in a non-predictable way!

Dissipative Structures • Equlibirum structure: • No effort to retain structure • Great effort to change structure • Dissipative structure: • Great effort to retain structure • Little effort to change structure When the water boils, a state of deterministic chaos In nature, as opposed to laboratory experiments, parameters are changed by nature itself. Self-organization is a process that occurs spontaneously at certain critical system values Such spontaneously moves to different attractors, only emerges when impacted from the environment The dissipative structure dissolves easily if the system moves away from critical parameter values

Dissipative Structures A wider implication of these identifications could be whether the future is given, or is it under perpetual construction? Prigogine: Nature is about the creation of unpredictable novelty, where the possible is richer than the real Life is a unstable system with an unknowable future in which the irreversibility of time plays a constitutive role

Dissipative Structures • If these theories were to be applied to an organization, then decision making processes that involved; • Forecasting • Envisioning future states • Making key assumptions about future states • .. would be problematic in terms of realizing a chosen future. Those applying such processes in conditions of stable instability would be engaging in fantasy activities • No one can establish how the system would move before a policy change and how it would move after the policy change. There would be no option, but to make the change and see what happens

Complex Adaptive Systems • CAS is characterized by a large number ofagents, each of which behaving to some set of rules. • These rules requires each agent to adjust its action to that of other agents and hence forming a system which also could be thought of as a population-wide pattern • Examples of Complex Adaptive Systems; • Bird flocking, where individual agents who might be following simple rules to do with adaption to the movement of neighbours so as to fly in formation without colliding • The human body, consisting of 30.000 individual genes interacting with each other to produce human physiology • An ecology with a number of species relating to each other to produce patterns of evolving life forms

Complex Adaptive Systems • Complexity sciences seeks to identify common features of the dynamics of the example systems in general • How do such complex non-linear systems function to produce orderly patterns across a population? • The expectation, when using traditionally sciences, for studying such phenomena's would be to identify laws governing evolution or blue-prints for the system • Scientists working with CAS take a fundamentally different approach: they model individual agent interaction with each agent behaving to its own local principles of interaction

Complex Adaptive Systems This leads to the principle of self-organization, agents interacts locally according to their own principles in the absence of an overall blueprint for the system they form Self-organization and emergence can lead to fundamental structural development (novelty), not just superficial change This is Spontaneous or Autonomous events, arising from the intrinsic iterative nonlinear nature of the system The inherent order in a CAS which evolves as the experience of the system, but no one can know what that evolutionary experience will be until it occurs

Complex Adaptive Systems Fitness Landscapes gives insight in evolutionary process, just as animals develops strategies to feed and survive To reach a peak means survival and to get trapped in a valley means extinction The peaks cannot beseen from lower levels Moving upwards through logicallyincremental strategymay fail due to missingcross-replication

Summary and perspective • Introduction to; • Chaos theory • Dissipative structures • Complex Adaptive Systems • A number of writers has been using these theories applied on organizations, however; • System views of interaction retained • Cognitivist approach to human psychology • Prescription of the manager as the objective observer • Overall a re-representation of SCT

Backup slides StaceyChapter 5

Systems DynamicsNonlinearity and Positive feedback Peter Senge is the father of Learning Organization Learning requires people to think in systems terms, in order to understand surroundings and leverage points Based on nonlinearity and positive feedback Nonlinearity occurs when some condition or action has varying effect on an outcome, depending on levels System dynamics may display the possibility to display non-equilibrium when flipping between +/- FB Cyclic behavior may occur and may be very irregular, if dependant on environmental fluctuations Important in understanding economic cycles and certain applications to organizations

Systems DynamicsPrinciples of systems dynamics Principles about Complex Human Systems: Complex systems often produces unexpected and counterintuitive results with nonlinear relationships, or with positive and negative feedback, the links between cause and effect are distant in time and space High sensitivity to some changes but remarkably insensitive to many other changes and these systems contain some influential pressure, or leverage points Managers can influence the system at these points, however they are difficult to identify Positive feedback (or regenerative feedback) occurs in a feedback loop when the mathematical sign of the net gain around the feedback loop is positive. That is, positive feedback is in phase with the input, in the sense that it adds to make the input larger. Positive feedback is a process in which the effects of a small disturbance on a system can include an increase in the magnitude of the perturbation

Animation of complex systems dynamics http://en.wikipedia.org/wiki/System_dynamics

Systems DynamicsCognitivist Psychology People who have personal mastery obtains the results they want and it commits to lifelong learning and may be linked to spiritual foundations Mental models are internal pictures of the external world. They are ingrained assumptions or generalisations often taking the form of pictures or images in individual minds, which often are hidden or unconscious mental constructions Management teams can change mental models and is cognitivist psychology as in SCT, which claims that humans are compelled to simplify everything observed Managers are humans as well and inevitably invent, so some extent, what they observe

Systems DynamicsConstructivist Psychology In Constructivist Psychology, people do not simply respond to stimuli about what is already there Rather, they select aspects of their environment according to their own identities and therefore enacting the environment relevant to them This is active cognition (recognising and responding) rather than passive (what is already there) Constructivist viewpoint because the world people act into is the world they have created by acting into it The shift in psychological model challenges SCT, however still focus on systems and individuals

Systems DynamicsEnactment and sensemaking Stimuli are placed in a framework so that they can comprehend, explain, extrapolate and predict Individuals form conscious and unconscious anticipations of what they expect to encounter.Sense- making is triggered encounters are different. The need for explanation is triggered by surprises and meaning is ascribed retrospectively Sense making is the process people employ to cope with interruptions of ongoing activity A distinction between collective and inter-subjective (individual-relating) forms of sense makig. Storytelling places cues for making sensne Novelty arises in dissonance, surprises, gaps etc.

Systems DynamicsSingle and double loop learning Single loop learning reuses previously acquired mental models for automating actions as unconscious processes Risk of skilled incompetence because unconscious models become taken for granted and requires stable environments Double loop learning occurs when actions are adjusted in the light of their consequences and questioning and adjusting the unconscious mental models used Possible difference between espoused and used models Managers often espouse rational models and at the same time other models as games for deception

Systems DynamicsSingle and double loop learning When mental models are questioned in double loop learning, fears arise because of the possibility to fail producing functioning alternatives to old models Defence routines – or covert politics – are activated, may end out in bland mission and vision statements The organization loses out on the creativity of people because of the management model it uses Managers must reflect jointly on the process they are engaged in, as a challenge, in order to be able to engage in double loop learning Double loop learning is then changing a mental model which again enables innovation

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