1. Build an Excel Spreadsheet Model
Build a spreadsheet to calculate the objective. You could model a project's net present value, the time to complete a project, etc.
2. Find Inputs to the Model that are Random Variables
Find the model inputs that can vary. These are called random variables and are a source of risk. Any single point estimates in your model are probably random variables.
3. Determine the Distribution of Each Random Variable
Determine the distribution, and parameters of each random variable. This may be based on expert estimates such as determining the minimum, most likely, and maximum task times when simulating a project critical path. If historical data is present, Simulation Master Premium's distribution fitting tool can be used to find the best fit distribution and its parameters.
4. Insert Simulation Master Random Variable Functions
Replace single point estimates in the model with Simulation Master's random variable functions. You can type functions directly in cells. If you can't remember a function's parameters, don't worry, there is a function assistant to guide you when adding random variable functions.
5. (Optional) Add Correlation
If random variable inputs are correlated, create a correlation matrix in the model, or use copulas to structure correlation among variables. Simulation Master has assistance tools to help add correlation structure to your model. There is a correlation matrix tool to easily add rank order correlation to your model. Copula functions can be entered directly in cells, or you can use the copula assistance tool to guide you.
6. Simulate the Model
Run a Monte Carlo simulation. Once finished, you'll see output statistics along with a histogram. You can analyze outcome probabilities now, or do it later. Simulation data can be saved in the Excel workbook in a separate worksheet.
7. Analyze the Output
Output summary statistics. Simulation Master generates summary statistics of the simulation output. These can be included in a summary report placed in the Excel workbook. Histogram, frequency polygon, and cumulative frequency charts of the output can also be included in the summary report.
Probability analysis of outcomes. The probability analysis tool determines probability of outcomes above/below a set-point or inside/outside of a range. Probability grab bars can be adjusted on the histogram to get a visual understanding of probabilities.
Correlation of inputs to output. The correlation tool will generate Pearson and Spearman Rank correlation coefficient values for each random variable with output. The tool will also generate tornado charts of the coefficients. This is useful for sensitivity analysis in determining which random variables have the most effect on output.
Scatter plots of inputs to output. The scatter plot tool will create scatter plots of random variables vs. output, and you can create scatter plots of random variable vs. random variable.
8. Present the Results
All charts and reports are native Excel objects so you can easily change formatting to meet your needs.