1. MSc. Project management RANEPA MOSCOW October 2017
PROFESSOR ROBIN MATTHEWS
KINGSTON UNIVERSITY BUSINESS SCHOOL LONDON
RANEPA MOSCOW
MOSI YOSHKAR-OLA
ECONOMIC STRATEGIES
PRESIDENT OF THE LEAGUE OF CORPORATE STRATEGY AND ACCOUNTING
http/
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2. ORGANIZATIONS ARE (COLLECTIONS OF) NETWORKS OF PROJECTS
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3. (current system state) T
Past
Future
upside
System state
possible futures
possible causes
probable futures
Probable causes
possible causes
possible futures
FUTURE
SCENARIOS
Now
(current system state) T
downside
PATH DEPENDENCE
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4. FUTURE SCENARIOS (outer dynamics) an example
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8. Complex adaptive systems can self organise spontaneously
1. continuous and dynamic interaction within and between levels of hierarchy 2. Non-linear interactions that are unpredictable; the scale of effects can’t be predicted for example. 3. Positive and negative feedbacks. 4. Large numbers of elements 5 open and closed systems 6. Co-evolution. 7. Unpredictable patterns emerge which become attractors influence future directions. 8. Attractors may be orderly or chaotic. 9. Far from equilibrium. 10. No single entity has complete knowledge of the system. 11. Path dependence. 12. adaptation through learning imagination. 13. Unpredictable time lags
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9. Rich pictures
Represent structures, processes & organisational issues relevant to the problem/issue.
What are the key issues
what problem to address
represent and communicate
Provide a way of thinking creatively; using emotion instinct and intuition and the intellect.
Attempt to use your artistic faculties.
Knowledge by presence rather than knowledge by correspondence.
Become aware of your mindsets;your habits of looking /thinking/ and decide
Antenarratives: before responses become habitual.
2. Problem situation not the problem itself
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13. META MODEL PAYOFFS Meta Model Mandala INNER DYNAMICS DYNAMICS GRAMMAR
OUTER
DYNAMICSOUTER
DYNAMICS
Meta Model
Mandala
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14. Assumption of definite goals & solutions
Hard problems
Problems well defined
Assumption of definite goals & solutions
Can pre-define success criteria
Technically/operationally oriented
Soft problems
Difficult to define - they are problem situations
High social, political & human activity component
Wicked
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15. Checkland’s Soft Systems Methodology
Premise
reality is socially constructed, therefore
requirements are not objective
systems thinking is not reductionist
Rationale
Problem/issues are fuzzy, unstructured often without solutions
defining the objective is part of the problem
Example
Integrated computerisation in the NHS largely failed. Why?
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16. Stage 1: Problem situation unstructured
Checkland’s Soft Systems Methodology
Stage 1: Problem situation unstructured
Stage 2: Problem situation expressed (rich pictures)
Stage 3: Naming of relevant systems (root definitions; CATWOE)
Stage 4: Conceptual models
Stage 5: Comparing conceptual models with reality
Stage 6: Debating feasible & desirable changes
Stage 7: Implementing changes
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17. organization grammar conceptual Action 17/11/2018 03:20:59
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18. RISK GRAMMAR SSM AND THE ENNEAGRAM MANDALA SSM AND THE ENNEAGRAM
OUTER DYNAMICS 9
GRAMMAR
Evaluation, 8
reflection
1 vision,
intention
SSM AND THE ENNEAGRAM MANDALA
Stage 5: Comparing conceptual models with reality
Stage 6: Debating feasible & desirable changes
Stage 7: Implementing changes
SSM AND THE ENNEAGRAM
MANDALA
Stage 1: Problem situation unstructured
Stage 2: Problem situation expressed (rich pictures)
Stage 3: Naming of relevant systems (root definitions; CATWOE)
Stage 4: Conceptual models
ADAPTATION
implementation 7
2 values
REALISATION
SEARCH
PAYOFFS 6
3 CAPABILITIES
choice commitment 5
4 alternative scenarios
GRAMMAR
RISK
GRAMMAR
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19. Global situation Postwar recovery 1945 – 70 Stagflation 1970 -1980
Keynesian policies
Stagflation
Monetarism and supply side economics 1980 – 2007
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20. GLOBAL POSITIVE FEEDBACKS
FINANCIAL
REVOLUTION
Flexible exchange rates
Deregulation
New asset pricing models
TECHNOLOGICAL
Investment funds
Shorter product cycles
Pressure to reduce costs
Outsourcing
GLOBAL
DEMAND
FDI
Consumption
Investment
Asset prices
Sovereign wealth funds
Securitization
GLOBAL POSITIVE FEEDBACKS
1980 – 2006
(circa)
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21. ENTROPY AND EVOLUTION EVOLUTION/EMERGENCE 17/11/2018 03:21:00
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22. The global economy as a complex adaptive system
The direction of the economy emerges from the interaction of many dispersed and interdependent units (firms, institutions, people, demographics, urbanization, cultures, religions, ethnicities personalities and so on) in parallel.
The action of any one unit depends on the state and action of others units.
The global economy has many levels of interaction; coalitions at many levels ranging from teams to business units and mergers.
Tangled interactions (associations, communications) occur within and between levels.
Coalitions are building blocks. They are recombined and revised continually as the system accumulates experience and adapts.
There are many niches created by new technologies that can be exploited by adaptation. Thus large and small local and global firms coexist and coevolve on the global economy; glocalisation.
There is no universal super-competitor, such as the USA or China or massive corporation or institution that can fill all niches; often they are helpless, global terrorism for example.
There are so many niches serving many purposes and needs the system operates far from equilibrium or optimum.
Despite the talk about progress and world growth recent developments have seen a resurgence of real politique; struggle for resources, struggle for dominance
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