Complexity Management 3r283q
This document was ed by and they confirmed that they have the permission to share it. If you are author or own the copyright of this book, please report to us by using this report form. Report r6l17
Overview 4q3b3c
& View Complexity Management as PDF for free.
More details 26j3b
- Words: 616
- Pages: 19
David Levy
Muhammad Taimur Shams Uddin Nighat Saif Safia Zeb Mustafa Kakakhel
To provide theoretical framework for dynamic evolution of industries
To provide application of Chaos theory in strategic management
To provide implication of Chaos theory for managerial purposes
Strategic management lacks theoretical tools to predict the behavior of firms and industries.
Industries evolve dynamically overtime due to actors’ interactions.
Existing theories assume simple linear relationships without .
Chaos theory provides useful conceptual framework accommodating the non linear complexity.
Chaos theory is the study of complex, non linear dynamic systems.
Butterfly effect
E.g. pendulum suspended between magnets
Tiny variations in initial position magnifies and results in chaotic behavior.
Predictability short term vs. long term
Industries are assumed to be dynamic, complex and non linear systems.
Interdependency of firms and industrial actors
Industries are non linear and are path dependant
So industries behave as chaotic systems
1.
Long term planning is very difficult
Smaller disturbances in initial state multiplies over time
Future forecasting is difficult due to complexity and non linear relationships.
Business should not spent on forecasting and strategic planning
2. Industries do no reach stable equilibrium
Traditional theories tries to reach stable equilibrium while equilibrium is not possible in chaotic system
Industries do not settle down and stability is not long lasting
E.g. Prices and investment patterns are short lived
3. Dramatic change can occur unexpectedly
Traditional theories suggest that small changes in parameters bring small changes in equilibrium Dramatic fluctuations occur internally in chaotic systems. Characteristic of probability distribution in chaotic systems. Small exogenous changes may also bring magnified fluctuations. E.g. New entrants or small change in technology
4. Short term forecasts are possible
Long term forecasting is difficult while short term forecasting is possible
This is because of the presence of patterns and fractals
The accurate models of complex system with carefully drawn initial points help in short term prediction
Chaotic systems shows repetitive patterns helping in forecasting
General guidelines are required since fixed strategies cannot be formulated for every scenario
Firms change their strategies as industrial structures evolve
Best strategies are those which achieve their goals even indirectly.
So we need dynamic strategies for coping with complexity and uncertainty
A model based on California Computer Technology is presented
This model demonstrates how chaotic theory can help in understanding real managerial issues
Supply chain as complex, dynamic and non linear system.
Two important dimensions
1. Uncertainty Each stage is exposed to shocks
Finished products fluctuate in volume to this uncertainty
The inventory need to be adjusted to cope with this uncertainty
2. Time Relationship
Disruption in one stage causes changes in other parts of the system
These disruption propagate forward and backward along the chain
This disruption causes chaos within the supply chain
Managers should make accurate sale forecasts to reduce cost of offshore manufacturing
Managers should deal with external factors like suppliers
Managers should reduce the occurrence of internal production problems
Managers should change the structure of supply chain accordingly
Chaos theory provides conceptual framework for the dynamic evolution of industries
Long term forecasting is almost impossible for chaotic systems
However short term forecasting is possible
Dramatic changes can occur unexpectedly
Chaos theory highlights the importance of guidelines formulation for coping with complexity
Underestimating complexity may result in unanticipated costs
Management might reduce the volatility of supply chain and improve its performance
Thank You
Muhammad Taimur Shams Uddin Nighat Saif Safia Zeb Mustafa Kakakhel
To provide theoretical framework for dynamic evolution of industries
To provide application of Chaos theory in strategic management
To provide implication of Chaos theory for managerial purposes
Strategic management lacks theoretical tools to predict the behavior of firms and industries.
Industries evolve dynamically overtime due to actors’ interactions.
Existing theories assume simple linear relationships without .
Chaos theory provides useful conceptual framework accommodating the non linear complexity.
Chaos theory is the study of complex, non linear dynamic systems.
Butterfly effect
E.g. pendulum suspended between magnets
Tiny variations in initial position magnifies and results in chaotic behavior.
Predictability short term vs. long term
Industries are assumed to be dynamic, complex and non linear systems.
Interdependency of firms and industrial actors
Industries are non linear and are path dependant
So industries behave as chaotic systems
1.
Long term planning is very difficult
Smaller disturbances in initial state multiplies over time
Future forecasting is difficult due to complexity and non linear relationships.
Business should not spent on forecasting and strategic planning
2. Industries do no reach stable equilibrium
Traditional theories tries to reach stable equilibrium while equilibrium is not possible in chaotic system
Industries do not settle down and stability is not long lasting
E.g. Prices and investment patterns are short lived
3. Dramatic change can occur unexpectedly
Traditional theories suggest that small changes in parameters bring small changes in equilibrium Dramatic fluctuations occur internally in chaotic systems. Characteristic of probability distribution in chaotic systems. Small exogenous changes may also bring magnified fluctuations. E.g. New entrants or small change in technology
4. Short term forecasts are possible
Long term forecasting is difficult while short term forecasting is possible
This is because of the presence of patterns and fractals
The accurate models of complex system with carefully drawn initial points help in short term prediction
Chaotic systems shows repetitive patterns helping in forecasting
General guidelines are required since fixed strategies cannot be formulated for every scenario
Firms change their strategies as industrial structures evolve
Best strategies are those which achieve their goals even indirectly.
So we need dynamic strategies for coping with complexity and uncertainty
A model based on California Computer Technology is presented
This model demonstrates how chaotic theory can help in understanding real managerial issues
Supply chain as complex, dynamic and non linear system.
Two important dimensions
1. Uncertainty Each stage is exposed to shocks
Finished products fluctuate in volume to this uncertainty
The inventory need to be adjusted to cope with this uncertainty
2. Time Relationship
Disruption in one stage causes changes in other parts of the system
These disruption propagate forward and backward along the chain
This disruption causes chaos within the supply chain
Managers should make accurate sale forecasts to reduce cost of offshore manufacturing
Managers should deal with external factors like suppliers
Managers should reduce the occurrence of internal production problems
Managers should change the structure of supply chain accordingly
Chaos theory provides conceptual framework for the dynamic evolution of industries
Long term forecasting is almost impossible for chaotic systems
However short term forecasting is possible
Dramatic changes can occur unexpectedly
Chaos theory highlights the importance of guidelines formulation for coping with complexity
Underestimating complexity may result in unanticipated costs
Management might reduce the volatility of supply chain and improve its performance
Thank You
Related Documents 171j1w
Complexity Management 3r283q
November 2022 0
The Complexity Of Songs 3v2n2o
December 2019 45
Chapter 1 - Complexity 2wr6s
October 2019 65
Observatory Of Economic Complexity 37116
September 2022 0
Project Complexity Calculator 236g6b
December 2019 50
Computational Complexity - Christos Papadimitriou.pdf 4c3l2k
November 2019 794More Documents from "mtaimur1" 411c59