Discrete-event simulation models an operation as a series of events over time — arrivals, processing, queueing, failures — capturing the randomness and interactions that simple spreadsheets miss. It lets you experiment on a digital model risk-free.
Simulation reveals emergent behavior like bottlenecks, queue buildup, and the effect of utilization and variability — and is the natural tool for validating a layout or staffing plan before committing capital. Monte Carlo is a related technique for uncertainty.