There's lots of things you can do with practical algorithms when you start thinking data-first approaches and try to fit the optimizations to the probability distribution of the data, i.e. fastest path for the most probable or important input and vice versa. Many approximations are based on the idea of ignoring input data which is improbable or has little effect on the outcome, and can be quite safely pruned out early.