Advanced Analytics

Our supreme discipline, our pet passion, our favorite toy. Just something completely unique and exactly what makes Level 4 so unique. Let’s demonstrate it by using the example of our national sport, football. Even better, let’s use the penalty shoot-out (apologies to our English website visitors). A report tells you, if the shot was a in or out (big deal, ey). If it is a really good report, it even tells you if the ball was kicked straight towards the goal, whether the ball hit the bar or the post, or if it missed the goal completely and even by how far. You could add another 20 facts but what you will never find out is exactly why the ball missed the goal. In order to do this we would need a whole series of penalties, all judged and measured in the same way with known results. In advanced analytics terms you would call this a test design. Now our data scientists can use the information and evaluate, with the help of multivariate statistical methods, the factors that are crucial for a goal or a miss. Speed, angle, preferences of the goalie – you name it. But that is not all. Our simulation models are capable of calibrating the identified influencing factors in such a way that the ball has the highest probability of going into the goal next time.

Back to business: ‘Advanced Analytics’ determine the critical success factors (cause and effect) and calibrate them for your maximal success (predictive modelling).