Modeling human decision behaviors for accurate prediction of project schedule duration

Simulation techniques have been widely applied in many disciplines to predict duration and cost of projects. However, as projects grew in size, they also grew in complexity making effective project planning a challenging task. Despite several attempts to achieve accurate predictions, simulation models in use are still considered to be oversimplified. They often fail to cope with uncertainty due to the complex modeling of the high number of interrelated factors. In this paper we propose a simulation model to cope with human resources uncertainty. We use the proxel-based simulation method to analyze and predict duration of project schedules exhibiting high uncertainty and typical human resources reallocation. The proxel-based simulation is an approximate simulation method that is proven to be more precise than discrete-event simulation. To model uncertainty, we introduce a new type of task, state-dependent (floating) task that supports and demonstrates a high degree of uncertainty in human resources allocation. In fact, it allows attributing different probability distributions to the same activity, depending on the team that may perform it. We use software development scheduling to illustrate our approach.