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The flapping of a butterflys wings in Brazil may make the difference between calm weather and a tornado in Texas next month Gleick 1987 In a shrinking world enabled by technology and typified by increasing degrees of integration across industries and regions relationships are stronger and the cascading effect of a small change is enormous in terms of both magnitude and speed In such a scenario where the future is unpredictable and the environment turbulent the postulates of traditional strategic thinking become increasingly anachronistic There is hence a need for a whole new paradigm that incorporates this uncertainty Chaos theory provides one such platform It suggests that complete and accurate information necessary for rational decision-making is unobtainable and the past is not an accurate guide to the future This article attempts to build a case for the application of chaos thinking to business strategy It identifies the key drivers of success in such an environment and goes on to develop a framework using which firms can hope to meet the challenges of a turbulent environment What is Chaos Theory Chaos theory studies complex and dynamic systems to reveal patterns of order out of seemingly chaotic behaviors These chaotic systems are characterized by excessive sensitivity to initial conditions It is based on the premise that there exists a non-linear relationship between causes and effects which implies that tiny causes can lead to big effects making it hard to predict the outcome of a change The principles of chaos theory have been successfully used to describe and explain diverse natural and artificial phenomena such as predicting epileptic seizures and financial markets modeling manufacturing systems and making weather forecasts In a scenario where businesses operate in a turbulent and unpredictable environment the tenets of chaos theory can be extremely valuable These are 1 It is possible to get completely random results from normal equations and 2 There is an underlying order in what appears to be completely random
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