The Butterfly Effect

The reading of this week once again directs attention to the old problem of reductionism. Over the fifties and sixties, the unreal optimism about weather forecasting was at its height. Even scientists like Von Neumann were speculating over control of the weather through the heightened understanding of the whole phenomenon. However, one thing that their endeavors were blind of was the possibility of chaos.

This line of reasoning was indeed stemming from the primacy of Approximation in natural science.  Approximation is regarded as modeling of nature through understanding of natural law, and attending to initial conditions of a system. What essentially happens through Approximation is reduction of the whole reality and overthrow of small influences, so that scientists are able to calculate the approximate behavior of a system. Approximation has been cornerstone of many sciences ranging from hard sciences (i.e. Physics) to human science (i.e. Economies). For instance, as with global weather forecasters, economists heavily rely upon this principle in their predication of systems’ behavior.

These models however cannot simplify what is really going on. The chapter states that in practice econometric models proved dismally blind to what the future would bring. These simplifications are employed since they are deemed to be better than nothing. Likewise, even though whether predications being engendered through these models can statically forecast a few days, they are incompetent when it comes to periods more than six or seven days.

Having scrutinized the patterns of the weather change, Edward Lorenz concluded that meager incidents can lead to thunderstorms or blizzards. In other words scanty uncertainties would multiply through an unknown and mysterious chain of turbulent future. His argument would inevitably imply that even the best kind of approximation brought about by the most advanced technologies would not be able to accommodate all these phenomena in its calculation. So there is no perfect approximation in existence.  System theory resonates with Lorenz’s conceptualizations. The universe as an open system comprises of infinite elements interacting with one another. One cannot grasp and predict the behavior of a system without examining all the delicate relationships between every single element and others. That is to say if some of these elements are left out in the assessment, we would lose the holistic view and any such prediction could not be totally conclusive.

The paper that I have chosen for this week is more or less an application oriented paper rather than a pure theoretical one.    It basically sheds light on problems of traditional supply chain management. One of the pivotal difficulties in this respect is “Bullwhip Effect.” The paper contends that the lack of information (what I call the lack of insight into the whole system) is taken as the main cause of “Bullwhip Effect.” This problem takes places where small fluctuations in every stage of supply chain become larger at every step up in the chain, from the customer through to the raw material suppliers. This effects result into increased raw material costs, overtime operations cost, additional transportation and warehousing const, and etc. I believe that this echoes what is implied by Butterfly effect where petite uncertainties magnify through the interaction of the system’s elements.  That is why manufacturers cannot oversee a great deal of patterns beyond immediate business patterns.

References:

• Lee, Hau L; Padmanabhan, V. and Whang, Seungjin (1997). "The Bullwhip Effect in Supply Chains". Sloan Management Review 38 (3): 93-102