ard Lorenz, can only be effectively modeled with an exact duplicate of itself. One example of a simple system to model is to calculate the time it takes for a train to go from city A to city B if it travels at a given speed. To predict the time we need only to know the speed that the train is traveling (in mph) and the distance (in miles). The simple formula would be mph/m, which is a simple system. But the pile of stones, which appears to be a simple system, is actually very complex. If we want to predict which stone will end up at which place in the pile then you would have to know very detailed information about the stones, including their weights, shapes, and starting location of each stone to make an accurate prediction. If there is a minor difference between the shape of one stone in the model and the shape of the original stone, the modeled results will be very different. The system is very complex, thus making prediction very difficult.. The generator of unpredictability in complex systems is what Lorenz calls "sensitivity to initial conditions" or "the butterfly effect." The concept means that with a complex, nonlinear system, a tiny difference in starting position can lead to greatly varied results. For example, in a difficult pool shot a tiny error in aim causes a slight change in the balls path. However, with each ball it collides with, the ball strays farther and farther from the intended path. Lorenz once said that "if a butterfly is flapping its wings in Argentina and we cannot take that action into account in our weather prediction, then we will fail to predict a thunderstorm over our home town two weeks from now because of this dynamic."(Lorenz, 1987) The general rule for complex systems is that one cannot create a model that will accurately predict outcomes but one can create models that simulate the processes that the system will go through to create the models. This realization is impacting many activities in busines...
