It seems virtually impossible to find a model for our decision-making which takes all details into account. In this episode we demonstrate how data abstraction can help to model a problem, thus making it the core of successful optimization.

Optimization projects are complex. How can we make sure, that our projects are going in the right direction? We divide our projects into 3 phases: the prototype, the minimum viable product and the fully productive product. Let’s see what the first phase is about and what we achieve with it.

Everything could be so simple if you only had one goal…. But unfortunately, you usually have several, which are also competing with each other. What is the best way to balance these goals?