When we look at the current economy and its goals, we can say that the modern labour force is more and more shifting in the direction of knowledge-intensive and decision-intensive jobs. Such jobs are based on the capabilities of workers to make decisions based on collected knowledge or information. Decision-intensive business processes consist of a phase where information is collected before a decision is taken in the subsequent phase. In our research we focus on dynamically optimizing how much information to collect in which order (Phase I), followed by optimizing the decision (Phase II). These two phases are dependent on each other. Collecting more information in Phase I is costly and asks for efficiency. The challenge is to choose which information to collect and, based on that new information, how to continue. Also, extra information allows to make a better decision in Phase II to improve the effectiveness. That is why we build models that can model the complex behaviour of the decision-intensive process and optimize such processes.