Demand forecasting
Moving Average Forecast
By the Supply Chain Manager team · Updated October 16, 2026
A moving average forecast predicts next period's demand as the average of the most recent periods, such as the last 7 or 14 days.
It is the simplest smoothing method. A longer window is steadier but slower to react; a shorter window reacts faster but follows noise. Every period in the window counts equally, which is the main difference from exponential smoothing.
How to calculate moving average
Forecast (next period) = (Demand₁ + Demand₂ + … + Demandₙ) ÷ n, using the last n periods
Moving average example
Illustrative numbers: daily sales of 12, 15, 9, 14, 10, 13 and 11 over the last week give a 7-day moving average of 12 units a day. A one-off 60-unit day would lift the next week's forecast by about 7 units a day until it drops out of the window.
Why moving average matters for distributors
For steady SKUs a moving average is often hard to beat, and it is easy to explain. It also makes a sensible benchmark for more complex models.
Common moving average mistakes
- Using it on trending or seasonal SKUs, where it always lags behind.
- Letting one-off bulk orders sit inside the window and inflate the forecast.
Moving average in Supply Chain Manager
Supply Chain Manager includes 7- and 14-day moving averages among the methods it backtests for each SKU.
Open the live demoExamples on this page use made-up round numbers to show the calculation. They are not benchmarks or results from real businesses.