What type of probability distribution is used for first-year demand?

• A. Normal distribution
• B. Uniform distribution
• C. Poisson distribution
• D. Exponential distribution

Answer: (A)

Modeling first-year demand with a normal distribution reflects the idea that demand is the result of many small, independent influences that aggregate to produce variability around a central forecast. The normal distribution is defined by a mean (your forecast) and a standard deviation (uncertainty), and it provides a symmetric spread of possible outcomes. In Monte Carlo simulations, sampling from this distribution lets you see how small Forecast errors propagate into revenue, costs, and profits, giving a realistic picture of risk around the expected demand.

Uniform would imply every value in a range is equally likely, which doesn’t match the typical situation where outcomes cluster around a forecast. Poisson is suitable for counting discrete events in a period, with variance tied to the mean, and is less appropriate for general first-year demand levels that aren’t just counts of rare events. Exponential describes time between events and is not a good fit for the level of demand in a period.