Monte Carlo Simulation

Monte Carlo Simulation is a quantitative risk analysis technique used in estimating activity durations. It involves running multiple simulations to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. When estimating activity durations, Monte Carlo Simulation helps assess the potential variability and uncertainty in estimates by generating a range of possible durations and their probabilities. In practice, the project manager defines probability distributions for the duration estimates of activities, considering best-case, most likely, and worst-case scenarios. The simulation then randomly samples values from these distributions and calculates the total project duration for each set of sampled values. By running thousands of iterations, the simulation builds a probability distribution of possible total project durations. This technique provides insights into the likelihood of completing the project within different time frames, helping project managers understand the risks associated with the schedule. It aids in identifying activities with high variability that may significantly impact the project timeline. Monte Carlo Simulation supports better decision-making by quantifying uncertainty and providing a probabilistic analysis of the schedule. By incorporating Monte Carlo Simulation into the estimation process, project managers can enhance the reliability of their schedules and develop contingency plans for potential delays.