|from : https://www.cis.upenn.edu/~cis501/papers/mooreslaw-reprint.pdf|
When looking at the performance improvement over the years there is a remarkable development. Martin Grötschel (actually it's work from Robert Bixby) reports a 43 million (!) fold speedup over a period of 15 years for one of the key algorithms in optimisation, the linear programming problem. Algorithms to solve linear programs are the most important ingredient of the techniques for solving combinatorial and integer programming problems. They are one of the key tools for an analytics consultant in solving real world decision problems. Grötschel shows that a benchmark production planning problem would take 85 years to solve on 1988 hard- and software, but that it can be solved within 1(!) minute using the latest hard- and software. Breaking the speedup down in machine independent speedup and the speedup of computing power shows that the progress in algorithms beats Moore’s law by a factor 43.
With trends like big data, decision models will increase in size and will become more optimisation driven. As Tom Davenport puts it “Although Analytics 3.0 includes all three types [descriptive, predictive, prescriptive], it emphasizes the last”. Davenport predicts that prescriptive models will be embedded into key processes and support us in our everyday decision making. This requires the models to be fast and robust. Technological progress is not the only power that enables this, it´s mathematics. And mathematics seems to have the upper hand on this,