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it would mean that it will work on a small scale as well as a large scale, and as the largest scales increase, it will still cope. If the size of an operation is X, then some algorithms, whatever they may do may be of an order of complexity of O(X) meaning it linearily increases computational dificulty in line with the size of it. whereas something of O(X^2) increases difficulty to the swaure of the size, so it would most likely grind to a halt if it became too large. on the other hand, an algorithm may be shown to have O(1) in that it is just as simple to calcuate no matter how large the underlying data set.
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