<p> Basic Simulation Model – Monte Carlo Method – with Excel</p><p>1. Process: Produce a RN from: 1. a table or dice 2. =RAND() 3. =RANDBETWEEN() 4. with a function and RN generator such as =norminv(rand(), σ, μ) 5. via tools/data analysis/random number generator</p><p>2. Process: Transform a RN through a table that sorts the RN into intervals based on occurrence. Obtain an input variable for the specific RN interval. In Excel use =vlookup or =hlookup tables. </p><p>3. Process: Use the input variable with a math (Linear programming), a financial, an accounting (P+L), a marketing (Proforma Income), a project management etc model to obtain an outcome corresponding to the specific input.</p><p>4. Process: Record in a table or column the specific outcome and continue to run the simulation by choosing a new RN and producing another outcome. The model moves forward based on the passage of a time interval (t+1) such as a new day or work shift or an event (n+1) occurring such as the arrival of a customer. The model proceeds to accumulate results until told to stop for some reason – say after 8 hours or after 100 events or a certain dollar amount is reached.</p><p>5. Process: Assess the table or column of results by means of descriptive statistics – mean, mode, median, max, min, stdev, count, countif etc, a formal, or better yet use CHART WIZARD to display a result. </p><p>6. Process: For maximum effect and excellence, run the simulation many times and gather summary results. Vary or range one of the key input parameters to see what effect it has on the model. Use DATA TABLES for this and also produce some more CHARTS.</p><p>7. Process: Verify model – examine for completeness, sensibility and stability. </p><p>8. Process: Recommend decision based on cost or profit criteria. Caution that the model is only as good as the numbers used and does not speak to any policy or executive decision process. ☺ - Peter Feb 05.</p>