Once you have created a simulation project, you are ready to run Risk Analysis to investigate the uncertainties within your model.
Simply identify the model variables that represent uncertainty. These variables are referred to as Assumptions. Then identify the variables for which you want to study the influence of the uncertainties. These variables are referred to as Effects. Choose between two different Risk algorithms; Monte-Carlo or Latin Hypercube.
Risk analysis is a built-in feature of Powersim Studio and is available by adding a Risk Analysis task:
Risk Analysis will give answers to how volatile your business strategies are when considering real-life uncertainties.
In the below example, a simulation model was used by a telecom company to plan when and how to increase their network capacity. The model considers different types of networks, staffing capacity, time to launch, and cost & revenue factors.
A Telecom simulation analyzing risk before expanding networks.
The end users ran multiple risk analyses to investigate how sensitive their business was to uncertainties in customer potential, complexity of network implementation, and its deterioration. The graphs show percentiles and standard deviation for one such Risk Analysis.
Benefits from using Risk Analysis in simulations