How do you test and validate decisions using simulations?

1 What are simulations?

Simulations are representations of real-world phenomena that use mathematical formulas, rules, and data to mimic their behavior and dynamics. Simulations can be simple or complex, depending on the level of detail and accuracy that you want to achieve. For example, you can simulate the motion of a pendulum using a simple equation, or you can simulate the climate of a planet using a sophisticated computer program.

2 Why use simulations for decision making?

Simulations can be a great way to test and validate decisions, as they provide valuable insights and feedback that might not be available through other methods. For instance, simulations can help you explore multiple alternatives and scenarios without risking real consequences or resources, identify potential risks or opportunities that may not be obvious, evaluate the impact of your actions over time, and learn from mistakes and successes to improve your understanding of the system.

3 How to design a simulation model?

When designing a simulation model, it is important to define the purpose and scope of the simulation, the variables and parameters of the system, the relationships and rules of the system, as well as the data sources and validation methods. Specifically, you need to consider what problem or question you are trying to address, what are the key factors and inputs that influence the behavior and outcomes of the system, how do variables and parameters interact and affect each other, and what are the sources and quality of the data used to populate and calibrate the model. Additionally, you must ensure that you have a valid method for verifying and testing the accuracy and reliability of your model.

4 How to run a simulation experiment?

In order to run a simulation experiment, you must first set up the initial conditions and parameters of the model, which should reflect the reality or scenario that you wish to simulate. After running the simulation and collecting the output data, you should analyze it and interpret the results. You should also take note of any patterns or trends that emerge. Finally, you can repeat the process with different conditions and parameters to determine how they affect the output and results.

5 How to communicate and apply the simulation results?

When communicating and applying the simulation results, you need to consider the audience and context, format and medium, limitations and uncertainties, and implications and recommendations. Who are the stakeholders and users of the simulation, and what are their needs and expectations? How do you present and deliver the simulation results, and what are the best ways to visualize and explain them? What are the sources and levels of error and variability in the simulation, and how do you acknowledge and address them? What are the main findings and insights from the simulation, and what are the actions or strategies that you suggest or support?

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?