What is the significance of the standard deviation in demand forecasting?

• A. It indicates the variability of demand around the mean
• B. It indicates the most likely demand level
• C. It measures the volatility of prices
• D. It is the average error of forecasts

Answer: (A)

Standard deviation captures how much demand fluctuates around its average, so it quantifies the uncertainty or dispersion in demand. In forecasting and planning, this matters because a higher standard deviation means demand is more volatile, requiring larger safety stock and wider forecast intervals to maintain service levels. For example, if the mean weekly demand is 100 units and the standard deviation is 20, you expect most weeks to fall within roughly 60 to 140 units (depending on the distribution), guiding how much inventory cushion to hold.

The most likely demand level is actually the mean, not the standard deviation, which is why the latter is not a measure of the most probable outcome. Price volatility concerns the fluctuation of prices, not demand itself, so the standard deviation of demand isn’t about prices. Lastly, the average error of forecasts is a separate accuracy metric (like RMSE or MAPE) that measures how far forecasts miss actual values, not how the actual values vary around the forecast.