And some of these cells include random numbers. With tabular simulations, you create your entire model in several cells in one row of a spreadsheet. Loosely speaking, we can divide stochastic simulations into two types, tabular and expanded. It’s time to bring stochastic modeling and forecasting in our work. It’s way past time for Excel users to reduce our reliance on deterministic simulations. This would have allowed us to specify our degree of uncertainty about each of our assumptions, and it also would have helped us to evaluate our uncertainty about our final results. On the other hand, what we should have been using was a stochastic simulation. Stochastic (or “probabilistic”) models rely on random numbers, typically drawn from a normal distribution.įrom this perspective, the type of simulation I prepared for my employers, and the type I saw in other companies was a deterministic simulation.Deterministic models use specific numbers for assumed values, including ratios.In general, there are two types of models: deterministic and probabilistic. The model represents the system itself, and the simulation represents the operation of the system over time. This model represents the key characteristics or behaviors of a system or process. The act of simulating something, Wikipedia explains, first requires that a model be developed. Wikipedia tells us that a simulation is the imitation of the operation of a real-world process or system over time. Since then, I’ve come to realize that most Excel models and forecasts are actually a form of simulation. And in all that time, I never saw a model, or forecast that could have done any better.
And they offered no way to assess or reduce my degree of uncertainty about my final forecast.Īnd also, during my years as an onsite Excel consultant, I saw many models and forecasts created by spreadsheet users from around the world. I knew that each predicted number in my forecast probably would land somewhere between a best-case and worst-case value…probably as determined by a normal distribution as shown in the Excel chart above.īut my models offered no way for me to include such probabilities.
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The second article is, How to Create Monte Carlo Models and Forecasts Using Excel Data Tables.)īack when I created models and forecasts for employers, I KNEW that my results were going to be wrong, and I had no practical way to express any degree of uncertainty in my results.įor example, if I were forecasting profits for a period, my spreadsheet would use one number for my forecast of sales in a period, another number for my forecast of operating expenses, another number for my cost-of-goods-sold percentage, and so on. (This is the first of two articles about normal distributions.
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